PROXIMITY-BASED SOCIAL GRAPH CREATION

Abstract

Systems and methods are disclosed for creating social connections. In general, a current crowd of a first user is monitored to detect if the current crowd matches an active interest of the first user. If the current crowd matches the active interest, a beacon is narrowcast to mobile devices of at least a subset of a number of other users in the current crowd of the first user. In one embodiment, the beacon is narrowcast to mobile devices of all of the other users in the current crowd. In another embodiment, the beacon is narrowcast to the mobile devices of only those other users having user profiles that include interests that match the active interest of the first user. Subsequently, a response to the beacon is received from a mobile device of a second user, and a new social connection is created between the first and second users.

Description

RELATED APPLICATIONS

This application claims the benefit of provisional patent application Ser. No. 61/173,625, filed Apr. 29, 2009, the disclosure of which is hereby incorporated herein by reference in its entirety.

FIELD OF THE DISCLOSURE

The present disclosure relates to creating new social connections between users in a social network.

BACKGROUND

Social graph creation is mostly done via existing social networking services such the Facebook® social networking service, the MySpace® social networking service, the LinkedIN® social networking service, and the Plaxo® social networking service. Nodes (i.e., people) and edges (i.e., relationships/connections) in social networks are manually defined by users of the social networking services. However, one issue is that relationships in these social networking services typically lag connections made between users in the real world. Thus, there is a need for a system and method that eases the burden on users to continually update their relationships in corresponding social networks in response to meeting new people in the real world.

SUMMARY

Systems and methods are disclosed for providing proximity-based social connection creation. In general, a current crowd of a first user is monitored to detect if the current crowd matches an active interest of the first user. If the current crowd matches the active interest of the first user, a beacon is narrowcast to mobile devices of at least a subset of a number of other users in the current crowd of the first user. In one embodiment, the beacon is narrowcast to mobile devices of all of the other users in the current crowd of the first user. In another embodiment, the beacon is narrowcast to the mobile devices of only those other users having user profiles that include interests that match the active interest of the first user. Subsequently, a response to the beacon is received from a mobile device of a second user. Upon receiving the response to the beacon, a new social connection is created between the first and second users.

In one embodiment, a current crowd of a first user is monitored to detect if the current crowd matches an active interest of the first user. If the current crowd matches the active interest of the first user, a two-way beacon is narrowcast to mobile devices of at least a subset of a number of other users in the current crowd of the first user. In one embodiment, the two-way beacon is narrowcast to mobile devices of all of the other users in the current crowd of the first user. In another embodiment, the two-way beacon is narrowcast to the mobile devices of only those other users having user profiles that include interests that match the active interest of the first user. Subsequently, a response to the two-way beacon is received from a mobile device of a second user. Upon receiving the response to the two-way beacon, a new two-way social connection between the first and second users is added to a social network. Optionally, out-of-band communication may be used to share a secret, such as a password, between the first user and the second user before adding the new two-way social connection to the social network.

In another embodiment, a current crowd of a first user is monitored to detect if the current crowd matches an active interest of the first user. If the current crowd matches the active interest of the first user, a one-way beacon is narrowcast to mobile devices of at least a subset of a number of other users in the current crowd of the first user. In one embodiment, the one-way beacon is narrowcast to mobile devices of all of the other users in the current crowd of the first user. In another embodiment, the one-way beacon is narrowcast to the mobile devices of only those other users having user profiles that include interests that match the active interest of the first user. Subsequently, a response to the one-way beacon is received from a mobile device of a second user. Upon receiving the response to the one-way beacon, a new tentative, or one-way, social connection between the first and second users is stored. In addition, in one embodiment, the new tentative social connection between the first and second users and one or more previous tentative social connections between the first and second users are analyzed in order to determine whether to recommend a two-way social connection between the first and second users. If a determination is made to recommend a two-way social connection, a recommendation is sent to a mobile device of the first user. If the first user accepts the recommendation, a new two-way social connection between the first and second users is added to a social network. Optionally, out-of-band communication may be used to share a secret, such as a password, between the first user and the second user before adding the new two-way social connection to the social network.

Those skilled in the art will appreciate the scope of the present invention and realize additional aspects thereof after reading the following detailed description of the preferred embodiments in association with the accompanying drawing figures.

BRIEF DESCRIPTION OF THE DRAWING FIGURES

The accompanying drawing figures incorporated in and forming a part of this specification illustrate several aspects of the invention, and together with the description serve to explain the principles of the invention.

FIG. 1 illustrates a Mobile Aggregate Profile (MAP) system according to one embodiment of the present disclosure;

FIG. 2 is a block diagram of the MAP server of FIG. 1 according to one embodiment of the present disclosure;

FIG. 3 is a block diagram of the MAP client of one of the mobile devices of FIG. 1 according to one embodiment of the present disclosure;

FIG. 4 illustrates the operation of the system of FIG. 1 to provide user profiles and current locations of the users of the mobile devices to the MAP server according to one embodiment of the present disclosure;

FIG. 5 illustrates the operation of the system of FIG. 1 to provide user profiles and current locations of the users of the mobile devices to the MAP server according to another embodiment of the present disclosure;

FIG. 6 is a flow chart for a spatial crowd formation process according to one embodiment of the present disclosure;

FIGS. 7A through 7D graphically illustrate the crowd formation process of FIG. 6 for an exemplary bounding box;

FIGS. 8A through 8D illustrate a flow chart for a spatial crowd formation process according to another embodiment of the present disclosure;

FIGS. 9A through 9D graphically illustrate the crowd formation process of FIGS. 8A through 8D for a scenario where the crowd formation process is triggered by a location update for a user having no old location;

FIGS. 10A through 10F graphically illustrate the crowd formation process of FIGS. 8A through 8D for a scenario where the new and old bounding boxes overlap;

FIGS. 11A through 11E graphically illustrate the crowd formation process of FIGS. 8A through 8D in a scenario where the new and old bounding boxes do not overlap;

FIG. 12 illustrates the operation of the system of FIG. 1 to create new two-way social connections using a two-way beacon according to one embodiment of the present disclosure;

FIG. 13 illustrates an exemplary Graphical User Interface (GUI) that enables a user to configure and initiate a two-way beacon request according to one embodiment of the present disclosure;

FIG. 14 illustrates an exemplary GUI for presenting an alert to a recipient of a two-way beacon according to one embodiment of the present disclosure;

FIG. 15 illustrates an exemplary GUI for presenting a secret to a responder to a two-way beacon to be used to formalize, or confirm, a new two-way social connection according to one embodiment of the present disclosure;

FIG. 16 illustrates an exemplary GUI that enables an initiator of a two-way beacon to enter a secret received from a responder to the two-way beacon via out-of-band communication in order to formalize, or confirm, a new two-way social connection according to one embodiment of the present disclosure;

FIG. 17 is a flow chart illustrating a process for sending a two-way beacon and creating a new two-way social connection based thereon according to one embodiment of the present disclosure;

FIG. 18 is a flow chart illustrating a more detailed process for creating a new two-way social connection between an initiator and a responder according to one embodiment of the present disclosure;

FIG. 19 illustrates the operation of the system of FIG. 1 to create social connections using a one-way beacon according to one embodiment of the present disclosure;

FIG. 20 is an exemplary GUI for presenting a recommendation to add a new two-way social connection according to one embodiment of the present disclosure;

FIG. 21 is a flow chart illustrating a process for sending a one-way beacon and creating a social connection based thereon according to one embodiment of the present disclosure;

FIG. 22 is a flow chart illustrating a process for creating a new tentative social connection between an initiator and a responder to a one-way beacon and, if appropriate, a new two-way social connection between the initiator and the responder according to one embodiment of the present disclosure;

FIG. 23 is a flow chart illustrating a process for generating an aggregate profile for a current crowd of an initiator of a beacon request according to one embodiment of the present disclosure;

FIG. 24 is a block diagram of the MAP server of FIG. 1 according to one embodiment of the present disclosure;

FIG. 25 is a block diagram of one of the mobile devices of FIG. 1 according to one embodiment of the present disclosure;

FIG. 26 is a block diagram of a server that operates to host one of the social networking services of FIG. 1 according to one embodiment of the present disclosure; and

FIG. 27 is a block diagram of a computing device that operates to host the third-party service of FIG. 1 according to one embodiment of the present disclosure.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The embodiments set forth below represent the necessary information to enable those skilled in the art to practice the invention and illustrate the best mode of practicing the invention. Upon reading the following description in light of the accompanying drawing figures, those skilled in the art will understand the concepts of the invention and will recognize applications of these concepts not particularly addressed herein. It should be understood that these concepts and applications fall within the scope of the disclosure and the accompanying claims.

FIG. 1 illustrates a Mobile Aggregate Profile (MAP) system 10 (hereinafter “system 10”) according to one embodiment of the present disclosure. In this embodiment, the system 10 includes a MAP server 12, one or more social networking services 14, a location server 16, a number of mobile devices 18-1 through 18-N having associated users 20-1 through 20-N, a subscriber device 22 having an associated subscriber 24, and a third-party service 26 communicatively coupled via a network 28. Note that the mobile devices 18-1 through 18-N are generally referred to herein as mobile devices 18. Likewise, the users 20-1 through 20-N are generally referred to herein as users 20. The network 28 may be any type of network or any combination of networks. Specifically, the network 28 may include wired components, wireless components, or both wired and wireless components. In one exemplary embodiment, the network 28 is a distributed public network such as the Internet, where the mobile devices 18-1 through 18-N are enabled to connect to the network 28 via local wireless connections (e.g., WiFi or IEEE 802.11 connections) or wireless telecommunications connections (e.g., 3G or 4G telecommunications connections such as GSM, LTE, W-CDMA, or WiMAX connections).

As discussed below in detail, the MAP server 12 operates to obtain current locations, including location updates, and user profiles of the users 20-1 through 20-N of the mobile devices 18-1 through 18-N. The current locations of the users 20-1 through 20-N can be expressed as positional geographic coordinates such as latitude-longitude pairs, and a height vector (if applicable), or any other similar information capable of identifying a given physical point in space in a two-dimensional or three-dimensional coordinate system. Using the current locations and user profiles of the users 20-1 through 20-N, the MAP server 12 may provide a number of features such as, but not limited to, maintaining a historical record of anonymized user profile data by location, generating aggregate profile data over time for a Point of Interest (POI) or Area of Interest (AOI) using the historical record of anonymized user profile data, identifying crowds of users using current locations and/or user profiles of the users 20-1 through 20-N, generating aggregate profiles for crowds of users at a POI or in an AOI using the current user profiles of users in the crowds, and crowd tracking. While not essential, for more information regarding the aforementioned features that may be provided by the MAP server 12, the interested reader is directed to U.S. patent application Ser. No. 12/645,535 entitled MAINTAINING A HISTORICAL RECORD OF ANONYMIZED USER PROFILE DATA BY LOCATION FOR USERS IN A MOBILE ENVIRONMENT, U.S. patent application Ser. No. 12/645,532 entitled FORMING CROWDS AND PROVIDING ACCESS TO CROWD DATA IN A MOBILE ENVIRONMENT, U.S. patent application Ser. No. 12/645,539 entitled ANONYMOUS CROWD TRACKING, U.S. patent application Ser. No. 12/645,544 entitled MODIFYING A USER'S CONTRIBUTION TO AN AGGREGATE PROFILE BASED ON TIME BETWEEN LOCATION UPDATES AND EXTERNAL EVENTS, U.S. patent application Ser. No. 12/645,546 entitled CROWD FORMATION FOR MOBILE DEVICE USERS, U.S. patent application Ser. No. 12/645,556 entitled SERVING A REQUEST FOR DATA FROM A HISTORICAL RECORD OF ANONYMIZED USER PROFILE DATA IN A MOBILE ENVIRONMENT, and U.S. patent application Ser. No. 12/645,560 entitled HANDLING CROWD REQUESTS FOR LARGE GEOGRAPHIC AREAS, all of which were filed on Dec. 23, 2009 and are hereby incorporated herein by reference in their entireties. Note that while the MAP server 12 is illustrated as a single server for simplicity and ease of discussion, it should be appreciated that the MAP server 12 may be implemented as a single physical server or multiple physical servers operating in a collaborative manner for purposes of redundancy and/or load sharing.

Importantly, in this embodiment, the MAP server 12 utilizes the current locations and user profiles of the users 20-1 through 20-N to create new social connections between the users 20-1 through 20-N in a social network(s) provided by the social networking service(s) 14. Note, however, that while the discussion herein focuses on an embodiment where the MAP server 12 creates new social connections, the present disclosure is not limited thereto. In another embodiment, a third-party service, such as the third-party service 26, may operate to create social connections between the users 20-1 through 20-N based on data obtained from the MAP server 12.

In general, the one or more social networking services 14 operate to store user profiles for a number of persons including the users 20-1 through 20-N of the mobile devices 18-1 through 18-N. For example, the one or more social networking services 14 may be social networking services such as the Facebook® social networking service, the MySpace® social networking service, the LinkedIN® social networking service, or the like. As discussed below, using the one or more social networking services 14, the MAP server 12 is enabled to directly or indirectly obtain the user profiles of the users 20-1 through 20-N of the mobile devices 18-1 through 18-N. The location server 16 generally operates to receive location updates from the mobile devices 18-1 through 18-N and make the location updates available to entities such as, for instance, the MAP server 12. In one exemplary embodiment, the location server 16 is a server operating to provide Yahoo!'s FireEagle service.

The mobile devices 18-1 through 18-N may be mobile smart phones, portable media player devices, mobile gaming devices, tablet computers, or the like. Some exemplary mobile devices that may be programmed or otherwise configured to operate as the mobile devices 18-1 through 18-N are the Apple® iPhone®, the Palm Pre™, the Samsung Rogue™, the Blackberry® Storm™, the Apple® iPod Touch® device, and the Apple® iPad™. However, this list of exemplary mobile devices is not exhaustive and is not intended to limit the scope of the present disclosure.

The mobile devices 18-1 through 18-N include MAP clients 30-1 through 30-N, MAP applications 32-1 through 32-N, third-party applications 34-1 through 34-N, and location functions 36-1 through 36-N, respectively. Using the mobile device 18-1 as an example, the MAP client 30-1 is preferably implemented in software. In general, in the preferred embodiment, the MAP client 30-1 is a middleware layer operating to interface an application layer (i.e., the MAP application 32-1 and the third-party applications 34-1) to the MAP server 12. More specifically, the MAP client 30-1 enables the MAP application 32-1 and the third-party applications 34-1 to request and receive data from the MAP server 12. In addition, the MAP client 30-1 enables applications, such as the MAP application 32-1 and the third-party applications 34-1, to access data from the MAP server 12. Note that while illustrated separately, some or all of the functionality of the MAP client 30-1 may be incorporated into the MAP application 32-1 and/or the third-party applications 34-1.

The MAP application 32-1 is also preferably implemented in software. The MAP application 32-1 generally provides a user interface component between the user 20-1 and the MAP server 12. More specifically, among other things, the MAP application 32-1 enables the user 20-1 to interact with the MAP server 12 for purposes of creating new social connections in the manner described below. In addition, the MAP application 32-1 may enable the user 20-1 to interface with the MAP server 12 to, for example, initiate historical requests for historical data or crowd requests for crowd data (e.g., aggregate profile data and/or crowd characteristics data) from the MAP server 12 for a POI or AOI. The MAP application 32-1 may also enable the user 20-1 to configure various settings. For example, the MAP application 32-1 may enable the user 20-1 to select one or more of the social networking services 14 from which to obtain the user profile of the user 20-1 and provide any necessary credentials (e.g., username and password) needed to access the user profile from the social networking service 14.

The third-party applications 34-1 are preferably implemented in software. The third-party applications 34-1 operate to access the MAP server 12 via the MAP client 30-1. The third-party applications 34-1 may utilize data obtained from the MAP server 12 in any desired manner. As an example, one of the third party applications 34-1 may be a gaming application that utilizes historical aggregate profile data to notify the user 20-1 of POIs or AOIs where persons having an interest in the game have historically congregated. It should be noted that while the discussion herein focuses on an embodiment where the users 20-1 through 20-N are enabled to interact with the MAP server 12 for purposes of creating new social connections, in another embodiment, the third-party applications 34-1 through 34-N may enable the users 20-1 through 20-N to interact with the MAP server 12 for purposes of creating new social connections.

The location function 36-1 may be implemented in hardware, software, or a combination thereof. In general, the location function 36-1 operates to determine or otherwise obtain the location of the mobile device 18-1. For example, the location function 36-1 may be or include a Global Positioning System (GPS) receiver.

The subscriber device 22 is a physical device such as a personal computer, a mobile computer (e.g., a notebook computer, a netbook computer, a tablet computer, etc.), a mobile smart phone, or the like. The subscriber 24 associated with the subscriber device 22 is a person or entity. In general, the subscriber device 22 enables the subscriber 24 to access the MAP server 12 via a web browser 38 to obtain various types of data, preferably for a fee. For example, the subscriber 24 may pay a fee to have access to historical aggregate profile data for one or more POIs and/or one or more AOIs, pay a fee to have access to crowd data such as aggregate profiles for crowds located at one or more POIs and/or located in one or more AOIs, pay a fee to track crowds, or the like. Note that the web browser 38 is exemplary. In another embodiment, the subscriber device 22 is enabled to access the MAP server 12 via a custom application.

Lastly, the third-party service 26 is a service that has access to data from the MAP server 12 such as a historical aggregate profile data for one or more POIs or one or more AOIs, crowd data such as aggregate profiles for one or more crowds at one or more POIs or within one or more AOIs, or crowd tracking data. Based on the data from the MAP server 12, the third-party service 26 operates to provide a service such as, for example, targeted advertising. For example, the third-party service 26 may obtain anonymous aggregate profile data for one or more crowds located at a POI and then provide targeted advertising to known users located at the POI based on the anonymous aggregate profile data. Note that while targeted advertising is mentioned as an exemplary third-party service 26, other types of third-party services 26 may additionally or alternatively be provided. Other types of third-party services 26 that may be provided will be apparent to one of ordinary skill in the art upon reading this disclosure.

Before proceeding, it should be noted that while the system 10 of FIG. 1 illustrates an embodiment where the one or more social networking services 14 and the location server 16 are separate from the MAP server 12, the present disclosure is not limited thereto. In an alternative embodiment, the functionality of the one or more social networking services 14 and/or the location server 16 may be implemented within the MAP server 12.

FIG. 2 is a block diagram of the MAP server 12 of FIG. 1 according to one embodiment of the present disclosure. As illustrated, the MAP server 12 includes an application layer 40, a business logic layer 42, and a persistence layer 44. The application layer 40 includes a user web application 46, a mobile client/server protocol component 48, and one or more data Application Programming Interfaces (APIs) 50. The user web application 46 is preferably implemented in software and operates to provide a web interface for users, such as the subscriber 24, to access the MAP server 12 via a web browser. The mobile client/server protocol component 48 is preferably implemented in software and operates to provide an interface between the MAP server 12 and the MAP clients 30-1 through 30-N hosted by the mobile devices 18-1 through 18-N. The data APIs 50 enable third-party services, such as the third-party service 26, to access the MAP server 12.

The business logic layer 42 includes a profile manager 52, a location manager 54, a history manager 56, a crowd analyzer 58, an aggregation engine 60, and a social connection manager 62, each of which is preferably implemented in software. The profile manager 52 generally operates to obtain the user profiles of the users 20-1 through 20-N directly or indirectly from the one or more social networking services 14 and store the user profiles in the persistence layer 44. The location manager 54 operates to obtain the current locations of the users 20-1 through 20-N including location updates. As discussed below, the current locations of the users 20-1 through 20-N may be obtained directly from the mobile devices 18-1 through 18-N and/or obtained from the location server 16.

The history manager 56 generally operates to maintain a historical record of anonymized user profile data by location. The crowd analyzer 58 operates to form crowds of users. In one embodiment, the crowd analyzer 58 utilizes a spatial crowd formation algorithm. However, the present disclosure is not limited thereto. In addition, the crowd analyzer 58 may further characterize crowds to reflect degree of fragmentation, best-case and worst-case degree of separation (DOS), and/or degree of bi-directionality. Still further, the crowd analyzer 58 may also operate to track crowds. The aggregation engine 60 generally operates to provide aggregate profile data in response to requests from the mobile devices 18-1 through 18-N, the subscriber device 22, and the third-party service 26. The aggregate profile data may be historical aggregate profile data for one or more POIs or one or more AOIs or aggregate profile data for crowd(s) currently at one or more POIs or within one or more AOIs. The social connection manager 62 generally operates to create new social connections between the users 20-1 through 20-N, as described below in detail. Note that social connections may also be referred to as edges in a social graph.

The persistence layer 44 includes an object mapping layer 64 and a datastore 66. The object mapping layer 64 is preferably implemented in software. The datastore 66 is preferably a relational database, which is implemented in a combination of hardware (i.e., physical data storage hardware) and software (i.e., relational database software). In this embodiment, the business logic layer 42 is implemented in an object-oriented programming language such as, for example, Java. As such, the object mapping layer 64 operates to map objects used in the business logic layer 42 to relational database entities stored in the datastore 66. Note that, in one embodiment, data is stored in the datastore 66 in a Resource Description Framework (RDF) compatible format.

In an alternative embodiment, rather than being a relational database, the datastore 66 may be implemented as an RDF datastore. More specifically, the RDF datastore may be compatible with RDF technology adopted by Semantic Web activities. Namely, the RDF datastore may use the Friend-Of-A-Friend (FOAF) vocabulary for describing people, their social networks, and their interests. In this embodiment, the MAP server 12 may be designed to accept raw FOAF files describing persons, their friends, and their interests. These FOAF files are currently output by some social networking services such as LiveJournal™ and Facebook®. The MAP server 12 may then persist RDF descriptions of the users 20-1 through 20-N as a proprietary extension of the FOAF vocabulary that includes additional properties desired for the MAP system 10.

FIG. 3 illustrates the MAP client 30-1 of FIG. 1 in more detail according to one embodiment of the present disclosure. This discussion is equally applicable to the other MAP clients 30-2 through 30-N. As illustrated, in this embodiment, the MAP client 30-1 includes a MAP access API 68, a MAP middleware component 70, and a mobile client/server protocol component 72. The MAP access API 68 is implemented in software and provides an interface by which the MAP client 30-1 and the third-party applications 34-1 are enabled to access the MAP client 30-1. The MAP middleware component 70 is implemented in software and performs the operations needed for the MAP client 30-1 to operate as an interface between the MAP application 32-1 and the third-party applications 34-1 at the mobile device 18-1 and the MAP server 12. The mobile client/server protocol component 72 enables communication between the MAP client 30-1 and the MAP server 12 via a defined protocol.

FIG. 4 illustrates the operation of the system 10 of FIG. 1 to provide the user profile of the user 20-1 of the mobile device 18-1 according to one embodiment of the present disclosure. This discussion is equally applicable to user profiles of the other users 20-2 through 20-N of the other mobile devices 18-2 through 18-N. First, an authentication process is performed (step 1000). For authentication, in this embodiment, the mobile device 18-1 authenticates with the social networking service 14 (step 1000A) and the MAP server 12 (step 1000B). In addition, the MAP server 12 authenticates with the social networking service 14 (step 1000C). Preferably, authentication is performed using OpenID or similar technology. However, authentication may alternatively be performed using separate credentials (e.g., username and password) of the user 20-1 for access to the MAP server 12 and the social networking service 14. Assuming that authentication is successful, the social networking service 14 returns an authentication succeeded message to the MAP server 12 (step 1000D), and the social networking service 14 returns an authentication succeeded message to the MAP client 30-1 of the mobile device 18-1 (step 1000E).

At some point after authentication is complete, a user profile process is performed such that a user profile of the user 20-1 is obtained from the social networking service 14 and delivered to the MAP server 12 (step 1002). In this embodiment, the MAP client 30-1 of the mobile device 18-1 sends a profile request to the social networking service 14 (step 1002A). In response, the social networking service 14 returns the user profile of the user 20-1 to the mobile device 18-1 (step 1002B). The MAP client 30-1 of the mobile device 18-1 then sends the user profile of the user 20-1 to the MAP server 12 (step 1002C). Note that while in this embodiment the MAP client 30-1 sends the complete user profile of the user 20-1 to the MAP server 12, in an alternative embodiment, the MAP client 30-1 may filter the user profile of the user 20-1 according to criteria specified by the user 20-1. For example, the user profile of the user 20-1 may include demographic information, general interests, music interests, and movie interests, and the user 20-1 may specify that the demographic information or some subset thereof is to be filtered, or removed, before sending the user profile to the MAP server 12.

Upon receiving the user profile of the user 20-1 from the MAP client 30-1 of the mobile device 18-1, the profile manager 52 of the MAP server 12 processes the user profile (step 1002D). More specifically, in the preferred embodiment, the profile manager 52 includes social network handlers for the social network services supported by the MAP server 12. Thus, for example, if the MAP server 12 supports user profiles from Facebook®, MySpace®, and LinkedIN®, the profile manager 52 may include a handler for Facebook®, a handler for MySpace®, and a handler for LinkedIN®. The social network handlers process user profiles to generate user profiles for the MAP server 12 that include lists of keywords for each of a number of profile categories. The profile categories may be the same for each of the social network handlers or different for each of the social network handlers. Thus, for this example assume that the user profile of the user 20-1 is from Facebook®. The profile manager 52 uses the handler for Facebook® to process the user profile of the user 20-1 to map the user profile of the user 20-1 from Facebook® to a user profile for the MAP server 12 including lists of keywords for a number of predefined profile categories. For example, for the handler for Facebook®, the profile categories may be a demographic profile category, a social interaction profile category, a general interests profile category, a music interests profile category, and a movie interests profile category. As such, the user profile of the user 20-1 from Facebook® may be processed by the corresponding handler of the profile manager 52 to create a list of keywords such as, for example, liberal, High School Graduate, 35-44, College Graduate, etc. for the demographic profile category; a list of keywords such as Seeking Friendship for the social interaction profile category; a list of keywords such as politics, technology, photography, books, etc. for the general interests profile category; a list of keywords including music genres, artist names, album names, or the like for the music interests profile category; and a list of keywords including movie titles, actor or actress names, director names, movie genres, or the like for the movie interests profile category. In one embodiment, the profile manager 52 may use natural language processing or semantic analysis. For example, if the Facebook® user profile of the user 20-1 states that the user 20-1 is 20 years old, semantic analysis may result in the keyword of 18-24 years old being stored in the user profile of the user 20-1 for the MAP server 12.

After processing the user profile of the user 20-1, the profile manager 52 of the MAP server 12 stores the resulting user profile for the user 20-1 (step 1002E). More specifically, in one embodiment, the MAP server 12 stores user records for the users 20-1 through 20-N in the datastore 66 (FIG. 2). The user profile of the user 20-1 is stored in the user record of the user 20-1. The user record of the user 20-1 includes a unique identifier of the user 20-1, the user profile of the user 20-1, and, as discussed below, a current location of the user 20-1. Note that the user profile of the user 20-1 may be updated as desired. For example, in one embodiment, the user profile of the user 20-1 is updated by repeating step 1002 each time the user 20-1 activates the MAP application 32-1.

Note that while the discussion herein focuses on an embodiment where the user profiles of the users 20-1 through 20-N are obtained from the one or more social networking services 14, the user profiles of the users 20-1 through 20-N may be obtained in any desired manner. For example, in one alternative embodiment, the user 20-1 may identify one or more favorite websites. The profile manager 52 of the MAP server 12 may then crawl the one or more favorite websites of the user 20-1 to obtain keywords appearing in the one or more favorite websites of the user 20-1. These keywords may then be stored as the user profile of the user 20-1.

At some point, a process is performed such that a current location of the mobile device 18-1 and thus a current location of the user 20-1 is obtained by the MAP server 12 (step 1004). In this embodiment, the MAP application 32-1 of the mobile device 18-1 obtains the current location of the mobile device 18-1 from the location function 36-1 of the mobile device 18-1. The MAP application 32-1 then provides the current location of the mobile device 18-1 to the MAP client 30-1, and the MAP client 30-1 then provides the current location of the mobile device 18-1 to the MAP server 12 (step 1004A). Note that step 1004A may be repeated periodically or in response to a change in the current location of the mobile device 18-1 in order for the MAP application 32-1 to provide location updates for the user 20-1 to the MAP server 12.

In response to receiving the current location of the mobile device 18-1, the location manager 54 of the MAP server 12 stores the current location of the mobile device 18-1 as the current location of the user 20-1 (step 1004B). More specifically, in one embodiment, the current location of the user 20-1 is stored in the user record of the user 20-1 maintained in the datastore 66 of the MAP server 12. Note that, in the preferred embodiment, only the current location of the user 20-1 is stored in the user record of the user 20-1. In this manner, the MAP server 12 maintains privacy for the user 20-1 since the MAP server 12 does not maintain a historical record of the location of the user 20-1. Any historical data maintained by the MAP server 12 may be anonymized in order to maintain the privacy of the users 20-1 through 20-N.

In addition to storing the current location of the user 20-1, the location manager 54 sends the current location of the user 20-1 to the location server 16 (step 1004C). In this embodiment, by providing location updates to the location server 16, the MAP server 12 in return receives location updates for the user 20-1 from the location server 16. This is particularly beneficial when the mobile device 18-1 does not permit background processes, which is the case for the Apple® iPhone. As such, if the mobile device 18-1 is an Apple® iPhone or similar device that does not permit background processes, the MAP application 32-1 will not be able to provide location updates for the user 20-1 to the MAP server 12 unless the MAP application 32-1 is active.

Therefore, when the MAP application 32-1 is not active, other applications running on the mobile device 18-1 (or some other device of the user 20-1) may directly or indirectly provide location updates to the location server 16 for the user 20-1. This is illustrated in step 1006 where the location server 16 receives a location update for the user 20-1 directly or indirectly from another application running on the mobile device 18-1 or an application running on another device of the user 20-1 (step 1006A). The location server 16 then provides the location update for the user 20-1 to the MAP server 12 (step 1006B). In response, the location manager 54 updates and stores the current location of the user 20-1 in the user record of the user 20-1 (step 1006C). In this manner, the MAP server 12 is enabled to obtain location updates for the user 20-1 even when the MAP application 32-1 is not active at the mobile device 18-1.

FIG. 5 illustrates the operation of the system 10 of FIG. 1 to provide the user profile of the user 20-1 of the mobile device 18-1 according to another embodiment of the present disclosure. This discussion is equally applicable to user profiles of the other users 20-2 through 20-N of the other mobile devices 18-2 through 18-N. First, an authentication process is performed (step 1100). For authentication, in this embodiment, the mobile device 18-1 authenticates with the MAP server 12 (step 1100A), and the MAP server 12 authenticates with the social networking service 14 (step 1100B). Preferably, authentication is performed using OpenID or similar technology. However, authentication may alternatively be performed using separate credentials (e.g., username and password) of the user 20-1 for access to the MAP server 12 and the social networking service 14. Assuming that authentication is successful, the social networking service 14 returns an authentication succeeded message to the MAP server 12 (step 1100C), and the MAP server 12 returns an authentication succeeded message to the MAP client 30-1 of the mobile device 18-1 (step 1100D).

At some point after authentication is complete, a user profile process is performed such that a user profile of the user 20-1 is obtained from the social networking service 14 and delivered to the MAP server 12 (step 1102). In this embodiment, the profile manager 52 of the MAP server 12 sends a profile request to the social networking service 14 (step 1102A). In response, the social networking service 14 returns the user profile of the user 20-1 to the profile manager 52 of the MAP server 12 (step 1102B). Note that while in this embodiment the social networking service 14 returns the complete user profile of the user 20-1 to the MAP server 12, in an alternative embodiment, the social networking service 14 may return a filtered version of the user profile of the user 20-1 to the MAP server 12. The social networking service 14 may filter the user profile of the user 20-1 according to criteria specified by the user 20-1. For example, the user profile of the user 20-1 may include demographic information, general interests, music interests, and movie interests, and the user 20-1 may specify that the demographic information or some subset thereof is to be filtered, or removed, before sending the user profile to the MAP server 12.

Upon receiving the user profile of the user 20-1, the profile manager 52 of the MAP server 12 processes the user profile (step 1102C). More specifically, as discussed above, in the preferred embodiment, the profile manager 52 includes social network handlers for the social networking services 14 supported by the MAP server 12. The social network handlers process user profiles to generate user profiles for the MAP server 12 that include lists of keywords for each of a number of profile categories. The profile categories may be the same for each of the social network handlers or different for each of the social network handlers.

After processing the user profile of the user 20-1, the profile manager 52 of the MAP server 12 stores the resulting user profile for the user 20-1 (step 1102D). More specifically, in one embodiment, the MAP server 12 stores user records for the users 20-1 through 20-N in the datastore 66 (FIG. 2). The user profile of the user 20-1 is stored in the user record of the user 20-1. The user record of the user 20-1 includes a unique identifier of the user 20-1, the user profile of the user 20-1, and, as discussed below, a current location of the user 20-1. Note that the user profile of the user 20-1 may be updated as desired. For example, in one embodiment, the user profile of the user 20-1 is updated by repeating step 1102 each time the user 20-1 activates the MAP application 32-1.

Note that while the discussion herein focuses on an embodiment where the user profiles of the users 20-1 through 20-N are obtained from the one or more social networking services 14, the user profiles of the users 20-1 through 20-N may be obtained in any desired manner. For example, in one alternative embodiment, the user 20-1 may identify one or more favorite websites. The profile manager 52 of the MAP server 12 may then crawl the one or more favorite websites of the user 20-1 to obtain keywords appearing in the one or more favorite websites of the user 20-1. These keywords may then be stored as the user profile of the user 20-1.

At some point, a process is performed such that a current location of the mobile device 18-1 and thus a current location of the user 20-1 is obtained by the MAP server 12 (step 1104). In this embodiment, the MAP application 32-1 of the mobile device 18-1 obtains the current location of the mobile device 18-1 from the location function 36-1 of the mobile device 18-1. The MAP application 32-1 then provides the current location of the user 20-1 of the mobile device 18-1 to the location server 16 (step 1104A). Note that step 1104A may be repeated periodically or in response to changes in the location of the mobile device 18-1 in order to provide location updates for the user 20-1 to the MAP server 12. The location server 16 then provides the current location of the user 20-1 to the MAP server 12 (step 1104B). The location server 16 may provide the current location of the user 20-1 to the MAP server 12 automatically in response to receiving the current location of the user 20-1 from the mobile device 18-1 or in response to a request from the MAP server 12.

In response to receiving the current location of the mobile device 18-1, the location manager 54 of the MAP server 12 stores the current location of the mobile device 18-1 as the current location of the user 20-1 (step 1104C). More specifically, in one embodiment, the current location of the user 20-1 is stored in the user record of the user 20-1 maintained in the datastore 66 of the MAP server 12. Note that, in the preferred embodiment, only the current location of the user 20-1 is stored in the user record of the user 20-1. In this manner, the MAP server 12 maintains privacy for the user 20-1 since the MAP server 12 does not maintain a historical record of the location of the user 20-1. As discussed below in detail, historical data maintained by the MAP server 12 may be anonymized in order to maintain the privacy of the users 20-1 through 20-N.

As discussed above, the use of the location server 16 is particularly beneficial when the mobile device 18-1 does not permit background processes, which is the case for the Apple® iPhone. As such, if the mobile device 18-1 is an Apple® iPhone or similar device that does not permit background processes, the MAP application 32-1 will not provide location updates for the user 20-1 to the location server 16 unless the MAP application 32-1 is active. However, other applications running on the mobile device 18-1 (or some other device of the user 20-1) may provide location updates to the location server 16 for the user 20-1 when the MAP application 32-1 is not active. This is illustrated in step 1106 where the location server 16 receives a location update for the user 20-1 from another application running on the mobile device 18-1 or an application running on another device of the user 20-1 (step 1106A). The location server 16 then provides the location update for the user 20-1 to the MAP server 12 (step 1106B). In response, the location manager 54 updates and stores the current location of the user 20-1 in the user record of the user 20-1 (step 1106C). In this manner, the MAP server 12 is enabled to obtain location updates for the user 20-1 even when the MAP application 32-1 is not active at the mobile device 18-1.

FIG. 6 begins a discussion of the operation of the crowd analyzer 58 to form crowds of users according to one embodiment of the present disclosure. Specifically, FIG. 6 is a flow chart for a spatial crowd formation process according to one embodiment of the present disclosure. Note that, in one embodiment, this process is performed in response to a request for crowd data (i.e., reactively). In another embodiment, this process may be performed proactively by the crowd analyzer 58 as, for example, a background process.

First, the crowd analyzer 58 establishes a bounding box for the crowd formation process (step 1200). Note that while a bounding box is used in this example, other geographic shapes may be used to define a bounding region for the crowd formation process (e.g., a bounding circle). In one embodiment, if crowd formation is performed in response to a specific request, the bounding box is established based on the request. For example, the request may identify a POI, in which case a bounding box of a predefined size that is centered at the POI is established. As another example, the request may identify an AOI, in which case a bounding box corresponding to the AOI is established. As yet another example, the request may identify a particular location, in which case a bounding box of a predefined size that is centered at that location is established. Alternatively, if the crowd formation process is performed proactively, the bounding box is a bounding box of a predefined size.

The crowd analyzer 58 then creates a crowd for each individual user in the bounding box (step 1202). More specifically, the crowd analyzer 58 queries the datastore 66 of the MAP server 12 to identify users currently located within the bounding box. Then, a crowd of one user is created for each user currently located within the bounding box. Next, the crowd analyzer 58 determines the two closest crowds in the bounding box (step 1204) and determines a distance between the two crowds (step 1206). The distance between the two crowds is a distance between crowd centers of the two crowds. Note that the crowd center of a crowd of one is the current location of the user in the crowd. The crowd analyzer 58 then determines whether the distance between the two crowds is less than an optimal inclusion distance (step 1208). In this embodiment, the optimal inclusion distance is a predefined static distance. If the distance between the two crowds is less than the optimal inclusion distance, the crowd analyzer 58 combines the two crowds (step 1210) and computes a new crowd center for the resulting crowd (step 1212). The crowd center may be computed based on the current locations of the users in the crowd using a center of mass algorithm. At this point the process returns to step 1204 and is repeated until the distance between the two closest crowds is not less than the optimal inclusion distance. At that point, the crowd analyzer 58 discards any crowds with less than three users (step 1214). Note that throughout this disclosure crowds are only maintained if the crowds include three or more users. However, while three users is the preferred minimum number of users in a crowd, the present disclosure is not limited thereto. The minimum number of users in a crowd may be defined as any number greater than or equal to two users.

FIGS. 7A through 7D graphically illustrate the crowd formation process of FIG. 6 for an exemplary bounding box 74. Crowds are noted by dashed circles, and the crowd centers are noted by cross-hairs (+). As illustrated in FIG. 7A, initially, the crowd analyzer 58 creates crowds 76 through 84 for the users in the geographic area, where, at this point, each of the crowds 76 through 84 includes one user. The current locations of the users are the crowd centers of the crowds 76 through 84. Next, the crowd analyzer 58 determines the two closest crowds and a distance between the two closest crowds. In this example, at this point, the two closest crowds are crowds 78 and 80, and the distance between the two closest crowds 78 and 80 is less than the optimal inclusion distance. As such, the two closest crowds 78 and 80 are combined by merging crowd 80 into crowd 78, and a new crowd center (+) is computed for the crowd 78, as illustrated in FIG. 7B. Next, the crowd analyzer 58 again determines the two closest crowds, which are now crowds 76 and 78. The crowd analyzer 58 then determines a distance between the crowds 76 and 78. Since the distance is less than the optimal inclusion distance, the crowd analyzer 58 combines the two crowds 76 and 78 by merging the crowd 76 into the crowd 78, and a new crowd center (+) is computed for the crowd 78, as illustrated in FIG. 7C. At this point, there are no more crowds separated by less than the optimal inclusion distance. As such, the crowd analyzer 58 discards crowds having less than three users, which in this example are crowds 82 and 84. As a result, at the end of the crowd formation process, the crowd 78 has been formed with three users, as illustrated in FIG. 7D.

FIGS. 8A through 8D illustrate a spatial crowd formation process according to another embodiment of the present disclosure. In this embodiment, the spatial crowd formation process is triggered in response to receiving a location update for one of the users 20-1 through 20-N and is preferably repeated for each location update received for the users 20-1 through 20-N. As such, first, the crowd analyzer 58 receives a location update, or a new location, for a user (step 1300). Assume that, for this example, the location update is received for the user 20-1. In response, the crowd analyzer 58 retrieves an old location of the user 20-1, if any (step 1302). The old location is the current location of the user 20-1 prior to receiving the new location. The crowd analyzer 58 then creates a new bounding box of a predetermined size centered at the new location of the user 20-1 (step 1304) and an old bounding box of a predetermined size centered at the old location of the user 20-1, if any (step 1306). The predetermined size of the new and old bounding boxes may be any desired size. As one example, the predetermined size of the new and old bounding boxes is 40 meters by 40 meters. Note that if the user 20-1 does not have an old location (i.e., the location received in step 1300 is the first location received for the user 20-1), then the old bounding box is essentially null. Also note that while bounding “boxes” are used in this example, the bounding areas may be of any desired shape.

Next, the crowd analyzer 58 determines whether the new and old bounding boxes overlap (step 1308). If so, the crowd analyzer 58 creates a bounding box encompassing the new and old bounding boxes (step 1310). For example, if the new and old bounding boxes are 40×40 meter regions and a 1×1 meter square at the northeast corner of the new bounding box overlaps a 1×1 meter square at the southwest corner of the old bounding box, the crowd analyzer 58 may create a 79×79 meter square bounding box encompassing both the new and old bounding boxes.

The crowd analyzer 58 then determines the individual users and crowds relevant to the bounding box created in step 1310 (step 1312). The crowds relevant to the bounding box are crowds that are within or overlap the bounding box (e.g., have at least one user located within the bounding box). The individual users relevant to the bounding box are users that are currently located within the bounding box and not already part of a crowd. Next, the crowd analyzer 58 computes an optimal inclusion distance for individual users based on user density within the bounding box (step 1314). More specifically, in one embodiment, the optimal inclusion distance for individuals, which is also referred to herein as an initial optimal inclusion distance, is set according to the following equation:

$\mathrm{initial\_optimal}\mathrm{\_inclusion}\mathrm{\_dist}=a·\sqrt{\frac{A_{\mathrm{BoundingBox}}}{\mathrm{number\_of}\mathrm{\_users}}},$

where a is a number between 0 and 1, A_BoundingBox is an area of the bounding box, and number_of_users is the total number of users in the bounding box. The total number of users in the bounding box includes both individual users that are not already in a crowd and users that are already in a crowd. In one embodiment, a is ⅔.

The crowd analyzer 58 then creates a crowd for each individual user within the bounding box that is not already included in a crowd and sets the optimal inclusion distance for the crowds to the initial optimal inclusion distance (step 1316). At this point, the process proceeds to FIG. 8B where the crowd analyzer 58 analyzes the crowds relevant to the bounding box to determine whether any of the crowd members (i.e., users in the crowds) violate the optimal inclusion distance of their crowds (step 1318). Any crowd member that violates the optimal inclusion distance of his or her crowd is then removed from that crowd (step 1320). The crowd analyzer 58 then creates a crowd of one user for each of the users removed from their crowds in step 1320 and sets the optimal inclusion distance for the newly created crowds to the initial optimal inclusion distance (step 1322).

Next, the crowd analyzer 58 determines the two closest crowds for the bounding box (step 1324) and a distance between the two closest crowds (step 1326). The distance between the two closest crowds is the distance between the crowd centers of the two closest crowds. The crowd analyzer 58 then determines whether the distance between the two closest crowds is less than the optimal inclusion distance of a larger of the two closest crowds (step 1328). If the two closest crowds are of the same size (i.e., have the same number of users), then the optimal inclusion distance of either of the two closest crowds may be used. Alternatively, if the two closest crowds are of the same size, the optimal inclusion distances of both of the two closest crowds may be used such that the crowd analyzer 58 determines whether the distance between the two closest crowds is less than the optimal inclusion distances of both of the two closest crowds. As another alternative, if the two closest crowds are of the same size, the crowd analyzer 58 may compare the distance between the two closest crowds to an average of the optimal inclusion distances of the two closest crowds.

If the distance between the two closest crowds is less than the optimal inclusion distance, the two closest crowds are combined or merged (step 1330), and a new crowd center for the resulting crowd is computed (step 1332). Again, a center of mass algorithm may be used to compute the crowd center of a crowd. In addition, a new optimal inclusion distance for the resulting crowd is computed (step 1334). In one embodiment, the new optimal inclusion distance for the resulting crowd is computed as:

$\mathrm{average}=\frac{1}{n+1}·\left(\mathrm{initial\_optimal}\mathrm{\_inclusion}\mathrm{\_dist}+\sum _{i=1}^nd_i\right),\mathrm{optimal\_inclusion}\mathrm{\_dist}=\mathrm{average}+\sqrt{\left(\frac{1}{n}·\sum _{i=1}^n{\left(d_i-\mathrm{average}\right)}^2\right)},$

where n is the number of users in the crowd and d_i is a distance between the ith user and the crowd center. In other words, the new optimal inclusion distance is computed as the average of the initial optimal inclusion distance and the distances between the users in the crowd and the crowd center plus one standard deviation.

At this point, the crowd analyzer 58 determines whether a maximum number of iterations have been performed (step 1336). The maximum number of iterations is a predefined number that ensures that the crowd formation process does not indefinitely loop over steps 1318 through 1334 or loop over steps 1318 through 1334 more than a desired maximum number of times. If the maximum number of iterations has not been reached, the process returns to step 1318 and is repeated until either the distance between the two closest crowds is not less than the optimal inclusion distance of the larger crowd or the maximum number of iterations has been reached. At that point, the crowd analyzer 58 discards crowds with less than three users, or members (step 1338), and the process ends.

Returning to step 1308 in FIG. 8A, if the new and old bounding boxes do not overlap, the process proceeds to FIG. 8C and the bounding box to be processed is set to the old bounding box (step 1340). In general, the crowd analyzer 58 then processes the old bounding box in much the same manner as described above with respect to steps 1312 through 1338. More specifically, the crowd analyzer 58 determines the individual users and crowds relevant to the bounding box (step 1342). The crowds relevant to the bounding box are crowds that are within or overlap the bounding box (e.g., have at least one user located within the bounding box). The individual users relevant to the bounding box are users that are currently located within the bounding box and not already part of a crowd. Next, the crowd analyzer 58 computes an optimal inclusion distance for individual users based on user density within the bounding box (step 1344). More specifically, in one embodiment, the optimal inclusion distance for individuals, which is also referred to herein as an initial optimal inclusion distance, is set according to the following equation:

$\mathrm{initial\_optimal}\mathrm{\_inclusion}\mathrm{\_dist}=a·\sqrt{\frac{A_{\mathrm{BoundingBox}}}{\mathrm{number\_of}\mathrm{\_users}}},$

where a is a number between 0 and 1, A_BoundingBox is an area of the bounding box, and number_of_users is the total number of users in the bounding box. The total number of users in the bounding box includes both individual users that are not already in a crowd and users that are already in a crowd. In one embodiment, a is ⅔.

The crowd analyzer 58 then creates a crowd of one user for each individual user within the bounding box that is not already included in a crowd and sets the optimal inclusion distance for the crowds to the initial optimal inclusion distance (step 1346). At this point, the crowd analyzer 58 analyzes the crowds for the bounding box to determine whether any crowd members (i.e., users in the crowds) violate the optimal inclusion distance of their crowds (step 1348). Any crowd member that violates the optimal inclusion distance of his or her crowd is then removed from that crowd (step 1350). The crowd analyzer 58 then creates a crowd of one user for each of the users removed from their crowds in step 1350 and sets the optimal inclusion distance for the newly created crowds to the initial optimal inclusion distance (step 1352).

Next, the crowd analyzer 58 determines the two closest crowds in the bounding box (step 1354) and a distance between the two closest crowds (step 1356). The distance between the two closest crowds is the distance between the crowd centers of the two closest crowds. The crowd analyzer 58 then determines whether the distance between the two closest crowds is less than the optimal inclusion distance of a larger of the two closest crowds (step 1358). If the two closest crowds are of the same size (i.e., have the same number of users), then the optimal inclusion distance of either of the two closest crowds may be used. Alternatively, if the two closest crowds are of the same size, the optimal inclusion distances of both of the two closest crowds may be used such that the crowd analyzer 58 determines whether the distance between the two closest crowds is less than the optimal inclusion distances of both of the two closest crowds. As another alternative, if the two closest crowds are of the same size, the crowd analyzer 58 may compare the distance between the two closest crowds to an average of the optimal inclusion distances of the two closest crowds.

If the distance between the two closest crowds is not less than the optimal inclusion distance of the larger of the two closest crowds, the process proceeds to step 1368. Otherwise, if the distance between the two closest crowds is less than the optimal inclusion distance, the two closest crowds are combined or merged (step 1360), and a new crowd center for the resulting crowd is computed (step 1362). Again, a center of mass algorithm may be used to compute the crowd center of a crowd. In addition, a new optimal inclusion distance for the resulting crowd is computed (step 1364). As discussed above, in one embodiment, the new optimal inclusion distance for the resulting crowd is computed as:

$\mathrm{average}=\frac{1}{n+1}·\left(\mathrm{initial\_optimal}\mathrm{\_inclusion}\mathrm{\_dist}+\sum _{i=1}^nd_i\right),\mathrm{optimal\_inclusion}\mathrm{\_dist}=\mathrm{average}+\sqrt{\left(\frac{1}{n}·\sum _{i=1}^n{\left(d_i-\mathrm{average}\right)}^2\right)},$

where n is the number of users in the crowd and d_i is a distance between the ith user and the crowd center. In other words, the new optimal inclusion distance is computed as the average of the initial optimal inclusion distance and the distances between the users in the crowd and the crowd center plus one standard deviation.

At this point, the crowd analyzer 58 determines whether a maximum number of iterations have been performed (step 1366). If the maximum number of iterations has not been reached, the process returns to step 1348 and is repeated until either the distance between the two closest crowds is not less than the optimal inclusion distance of the larger crowd or the maximum number of iterations has been reached. At that point, the crowd analyzer 58 discards crowds with less than three users, or members (step 1368). The crowd analyzer 58 then determines whether the crowd formation process for the new and old bounding boxes is done (step 1370). In other words, the crowd analyzer 58 determines whether both the new and old bounding boxes have been processed. If not, the bounding box is set to the new bounding box (step 1372), and the process returns to step 1342 and is repeated for the new bounding box. Once both the new and old bounding box have been processed, the crowd formation process ends.

FIGS. 9A through 9D graphically illustrate the crowd formation process of FIGS. 8A through 8D for a scenario where the crowd formation process is triggered by a location update for a user having no old location. In this scenario, the crowd analyzer 58 creates a new bounding box 86 for the new location of the user, and the new bounding box 86 is set as the bounding box to be processed for crowd formation. Then, as illustrated in FIG. 9A, the crowd analyzer 58 identifies all individual users currently located within the bounding box 86 and all crowds located within or overlapping the bounding box. In this example, crowd 88 is an existing crowd relevant to the bounding box 86. Crowds are indicated by dashed circles, crowd centers are indicated by cross-hairs (+), and users are indicated as dots. Next, as illustrated in FIG. 9B, the crowd analyzer 58 creates crowds 90 through 94 of one user for the individual users, and the optional inclusion distances of the crowds 90 through 94 are set to the initial optimal inclusion distance. As discussed above, the initial optimal inclusion distance is computed by the crowd analyzer 58 based on a density of users within the bounding box 86.

The crowd analyzer 58 then identifies the two closest crowds 90 and 92 in the bounding box 86 and determines a distance between the two closest crowds 90 and 92. In this example, the distance between the two closest crowds 90 and 92 is less than the optimal inclusion distance. As such, the two closest crowds 90 and 92 are merged and a new crowd center and new optimal inclusion distance are computed, as illustrated in FIG. 9C. The crowd analyzer 58 then repeats the process such that the two closest crowds 90 and 94 in the bounding box 86 are again merged, as illustrated in FIG. 9D. At this point, the distance between the two closest crowds 88 and 90 is greater than the appropriate optimal inclusion distance. As such, the crowd formation process is complete.

FIGS. 10A through 10F graphically illustrate the crowd formation process of FIGS. 8A through 8D for a scenario where the new and old bounding boxes overlap. As illustrated in FIG. 10A, a user moves from an old location to a new location, as indicated by an arrow. The crowd analyzer 58 receives a location update for the user giving the new location of the user. In response, the crowd analyzer 58 creates an old bounding box 96 for the old location of the user and a new bounding box 98 for the new location of the user. Crowd 100 exists in the old bounding box 96, and crowd 102 exists in the new bounding box 98.

Since the old bounding box 96 and the new bounding box 98 overlap, the crowd analyzer 58 creates a bounding box 104 that encompasses both the old bounding box 96 and the new bounding box 98, as illustrated in FIG. 10B. In addition, the crowd analyzer 58 creates crowds 106 through 112 for individual users currently located within the bounding box 104. The optimal inclusion distances of the crowds 106 through 112 are set to the initial optimal inclusion distance computed by the crowd analyzer 58 based on the density of users in the bounding box 104.

Next, the crowd analyzer 58 analyzes the crowds 100, 102, and 106 through 112 to determine whether any members of the crowds 100, 102, and 106 through 112 violate the optimal inclusion distances of the crowds 100, 102, and 106 through 112. In this example, as a result of the user leaving the crowd 100 and moving to his new location, both of the remaining members of the crowd 100 violate the optimal inclusion distance of the crowd 100. As such, the crowd analyzer 58 removes the remaining users from the crowd 100 and creates crowds 114 and 116 of one user each for those users, as illustrated in FIG. 10C.

The crowd analyzer 58 then identifies the two closest crowds in the bounding box 104, which in this example are the crowds 110 and 112. Next, the crowd analyzer 58 computes a distance between the two crowds 110 and 112. In this example, the distance between the two crowds 110 and 112 is less than the initial optimal inclusion distance and, as such, the two crowds 110 and 112 are combined. In this example, crowds are combined by merging the smaller crowd into the larger crowd. Since the two crowds 110 and 112 are of the same size, the crowd analyzer 58 merges the crowd 112 into the crowd 110, as illustrated in FIG. 10D. A new crowd center and new optimal inclusion distance are then computed for the crowd 110.

At this point, the crowd analyzer 58 repeats the process and determines that the crowds 102 and 108 are now the two closest crowds. In this example, the distance between the two crowds 102 and 108 is less than the optimal inclusion distance of the larger of the two crowds 102 and 108, which is the crowd 102. As such, the crowd 108 is merged into the crowd 102 and a new crowd center and optimal inclusion distance are computed for the crowd 102, as illustrated in FIG. 10E. At this point, there are no two crowds closer than the optimal inclusion distance of the larger of the two crowds. As such, the crowd analyzer 58 discards any crowds having less than three members, as illustrated in FIG. 10F. In this example, the crowds 106, 110, 114, and 116 have less than three members and are therefore removed. The crowd 102 has three or more members and, as such, is not removed. At this point, the crowd formation process is complete.

FIGS. 11A through 11E graphically illustrate the crowd formation process of FIGS. 8A through 8D in a scenario where the new and old bounding boxes do not overlap. As illustrated in FIG. 11A, in this example, the user moves from an old location to a new location. The crowd analyzer 58 creates an old bounding box 118 for the old location of the user and a new bounding box 120 for the new location of the user. Crowds 122 and 124 exist in the old bounding box 118, and crowd 126 exists in the new bounding box 120. In this example, since the old and new bounding boxes 118 and 120 do not overlap, the crowd analyzer 58 processes the old and new bounding boxes 118 and 120 separately.

More specifically, as illustrated in FIG. 11B, as a result of the movement of the user from the old location to the new location, the remaining users in the crowd 122 no longer satisfy the optimal inclusion distance for the crowd 122. As such, the remaining users in the crowd 122 are removed from the crowd 122, and crowds 128 and 130 of one user each are created for the removed users as shown in FIG. 11C. In this example, no two crowds in the old bounding box 118 are close enough to be combined. As such, processing of the old bounding box 118 is complete, and the crowd analyzer 58 proceeds to process the new bounding box 120.

As illustrated in FIG. 11D, processing of the new bounding box 120 begins by the crowd analyzer 58 creating a crowd 132 of one user for the user that moved. The crowd analyzer 58 then identifies the crowds 126 and 132 as the two closest crowds in the new bounding box 120 and determines a distance between the two crowds 126 and 132. In this example, the distance between the two crowds 126 and 132 is less than the optimal inclusion distance of the larger crowd, which is the crowd 126. As such, the crowd analyzer 58 combines the crowds 126 and 132 by merging the crowd 132 into the crowd 126, as illustrated in FIG. 11E. A new crowd center and new optimal inclusion distance are then computed for the crowd 126. At this point, the crowd formation process is complete.

Before proceeding, a variation of the spatial formation process discussed above with respect to FIGS. 8A through 8D, 9A through 9D, 10A through 10F, and 11A through 11E will be described. In this alternative embodiment, a location accuracy of the location update from the user received in step 1300 is considered. More specifically, in step 1300, the location update received by the MAP server 12 includes the updated location of the user 20-1 as well as a location accuracy for the location of the user 20-1, which may be expressed as, for example, a radius in meters from the location of the user 20-1. In the embodiment where the location of the user 20-1 is obtained from a GPS receiver of the mobile device 18-1, the location accuracy of the location of the user 20-1 may be provided by the GPS receiver or derived from data from the GPS receiver as will be appreciated by one having ordinary skill in the art.

Then, in steps 1302 and 1304, sizes of the new and old bounding boxes centered at the new and old locations of the user 20-1 are set as a function of the location accuracy of the new and old locations of the user 20-1. If the new location of the user 20-1 is inaccurate, then the new bounding box will be large. If the new location of the user 20-1 is accurate, then the new bounding box will be small. For example, the length and width of the new bounding box may be set to M times the location accuracy of the new location of the user 20-1, where the location accuracy is expressed as a radius in meters from the new location of the user 20-1. The number M may be any desired number. For example, the number M may be 5. In a similar manner, the location accuracy of the old location of the user 20-1 may be used to set the length and width of the old bounding box.

In addition, the location accuracy may be considered when computing the initial optimal inclusion distances used for crowds of one user in steps 1314 and 1344. As discussed above, the initial optimal inclusion distance is computed based on the following equation:

$\mathrm{initial\_optimal}\mathrm{\_inclusion}\mathrm{\_dist}=a·\sqrt{\frac{A_{\mathrm{BoundingBox}}}{\mathrm{number\_of}\mathrm{\_users}}},$

where a is a number between 0 and 1, A_BoundingBox is an area of the bounding box, and number_of_users is the total number of users in the bounding box. The total number of users in the bounding box includes both individual users that are not already in a crowd and users that are already in a crowd. In one embodiment, a is ⅔. However, if the computed initial optimal inclusion distance is less than the location accuracy of the current location of the individual user in a crowd, then the location accuracy, rather than the computed value, is used for the initial optimal inclusion distance for that crowd. As such, as location accuracy decreases, crowds become larger and more inclusive. In contrast, as location accuracy increases, crowds become smaller and less inclusive. In other words, the granularity with which crowds are formed is a function of the location accuracy.

Likewise, when new optimal inclusion distances for crowds are recomputed in steps 1334 and 1364, location accuracy may also be considered. As discussed above, the new optimal inclusion distance may first be computed based on the following equation:

$\mathrm{average}=\frac{1}{n+1}·\left(\mathrm{initial\_optimal}\mathrm{\_inclusion}\mathrm{\_dist}+\sum _{i=1}^nd_i\right),\mathrm{optimial\_inclusion}\mathrm{\_dist}=\mathrm{average}+\sqrt{\left(\frac{1}{n}·\sum _{i=1}^n{\left(d_i-\mathrm{average}\right)}^2\right)},$

where n is the number of users in the crowd and d_i is a distance between the ith user and the crowd center. In other words, the new optimal inclusion distance is computed as the average of the initial optimal inclusion distance and the distances between the users in the crowd and the crowd center plus one standard deviation. However, if the computed value for the new optimal inclusion distance is less than an average location accuracy of the users in the crowd, the average location accuracy of the users in the crowd, rather than the computed value, is used as the new optimal inclusion distance.

FIG. 12 illustrates the operation of the system 10 of FIG. 1 to create new two-way social connections between the users 20-1 through 20-N according to one embodiment of the present disclosure. First, the mobile device 18-1 sends a two-way beacon request to the MAP server 12 (step 1400). More specifically, in one embodiment, the MAP application 32-1 enables the user 20-1 to input a number of two-way beacon configurations, or settings. The two-way beacon configurations include one or more active interests of the user 20-1. The active interests are preferably one or more interests from the user profile of the user 20-1, but are not limited thereto. In addition, the two-way beacon configurations may include a pseudonym to be used in lieu of the actual name, username, or other identifying data of the user 20-1 when narrowcasting the two-way beacon, as discussed below. Once the user 20-1 inputs the two-way beacon configurations, the user 20-1 initiates sending of the two-way beacon request, and, in response, the MAP application 32-1 sends the two-way beacon request including the two-way beacon configurations to the MAP server 12. Note that the user 20-1 of the mobile device 18-1 is also referred to herein as the initiator of the two-way beacon request.

An exemplary Graphical User Interface (GUI) 134 that may be provided by the MAP application 32-1 to enable the user 20-1 to input the two-way beacon configurations and initiate the two-way beacon request is illustrated in FIG. 13. As illustrated, the GUI 134 includes radio buttons 136 and 138 that allow the user 20-1 to enable or disable the social connection creation process with respect to the user 20-1. In addition, the GUI 134 includes a check box 140 that, when selected, enables the user 20-1 to define or otherwise select a pseudonym to be used in lieu of the name, username, or other identifying information when narrowcasting the two-way beacon. In this example, the pseudonym is entered via a text field 142. The GUI 134 also includes a field 144 that enables the user 20-1 to select or otherwise define the active interest for the two-way beacon request. The GUI 134 also includes radio buttons 146 and 148 that enable the user 20-1 to configure the beacon as either a two-way beacon or a one-way beacon (discussed below), respectively. Lastly, the GUI 134 includes an OK button 150 and a Cancel button 152. The user 20-1 configures the two-way beacon request by selecting the radio button 136 to enable the social connection creation process, defining a pseudonym if desired, defining the active interest in the field 144, and selecting the two-way radio button 146. The user 20-1 then initiates the two-way beacon request by selecting the OK button 150.

Returning to FIG. 12, in response to receiving the two-way beacon request, the social connection manager 62 of the MAP server 12 detects when a current crowd of the user 20-1 matches the active interest of the user 20-1, which is included in the two-way beacon configurations (step 1402). More specifically, in one embodiment, the social connection manager 62 periodically obtains an aggregate profile of a current crowd in which the user 20-1 is located. The current crowd in which the user 20-1 is located may be identified by the crowd analyzer 58 by periodically performing the spatial crowd formation process of FIG. 6 for a geographic region encompassing the current location of the user 20-1. Alternatively, the crowd analyzer 58 may proactively perform the spatial crowd formation process of FIGS. 8A through 8D such that the current crowd of the user 20-1 can be identified by querying the datastore 66 of the MAP server 12. As discussed below, in one embodiment, the aggregate profile of the current crowd is generated by comparing the active interest of the user 20-1 to the user profiles of the other users in the current crowd of the user 20-1. The aggregate profile of the current crowd preferably includes a number of user matches for the active interest in the current crowd or a ratio of the number of user matches for the active interest to a total number of users in the current crowd. For purposes of generating the aggregate profile, the total number of users in the current crowd of the user 20-1 may be the number of users in the current crowd other than the user 20-1. The social connection manager 62 then determines whether the current crowd matches the active interest of the user 20-1 based on the aggregate profile of the current crowd. For example, in one embodiment, there is a match if the number of user matches or the ratio of the number of user matches to the total number of users in the current crowd is greater than a predefined threshold. The predefined threshold may be configurable by the user 20-1 or may be system-defined.

In response to detecting there is a match between the current crowd of the user 20-1 and the active interest of the user 20-1, the social connection manager 62 of the MAP server 12 narrowcasts a two-way beacon to at least a subset of the current crowd of the user 20-1 (step 1404). In one embodiment, the social connection manager 62 narrowcasts the two-way beacon to all of the other users in the current crowd of the user 20-1. In another embodiment, the social connection manager 62 narrowcasts the two-way beacon to only those other users in the current crowd of the user 20-1 having user profiles that include interests that match the active interest of the user 20-1. For an interest to match the active interest of the user 20-1, the interest may be required to exactly match the active interest or may only be required to match the active interest at least to a predetermined threshold degree. For example, an interest may be determined to match the active interest of the user 20-1 if the interest is sufficiently similar to the active interest of the user 20-1 as determined via natural language processing (e.g., “NC State” matches “North Carolina State University”). As another example, an interest may be determined to match the active interest of the user 20-1 if the interest is related to the active interest within a predefined maximum number of degrees of separation in an ontology or similar data structure (e.g., “George Lucas” within a user-defined or system-defined maximum number of “hops” or degrees of separation from “Star Wars” in the ontology such that these two interests are determined to match). Whether the two-way beacon is narrowcast to all of the other users in the current crowd of the user 20-1 or only to those other users in the current crowd of the user 20-1 having user profiles that include interests that match the active interest of the user 20-1, the two-way beacon is not narrowcast or otherwise sent to users outside of the current crowd of the user 20-1.

In this example, the user 20-N of the mobile device 18-N is in the current crowd of the user 20-1, and the two-way beacon is narrowcast to the mobile device 18-N of the user 20-N. Note that the two-way beacon is also narrowcast to the mobile devices 18 of other users 20 in the current crowd of the user 20-1. However, only the mobile device 18-N is illustrated for clarity and ease of discussion. The two-way beacon may be narrowcast using any suitable technology. In this embodiment, the two-way beacon is narrowcast to the mobile device 18-N via a dedicated communication session or link between the MAP server 12 and the MAP application 32-N of the mobile device 18-N over the network 28. However, other techniques for narrowcasting the two-way beacon may be used (e.g., SMS or MMS message). In response to receiving the two-way beacon, the mobile device 18-N presents an alert corresponding to the two-way beacon to the user 20-N (step 1406). In one embodiment, the alert is presented via the MAP application 32-N.

FIG. 14 illustrates an exemplary GUI 154 for presenting the alert to the user 20-N in response to receiving the two-way beacon at the mobile device 18-N according to an exemplary embodiment of the present disclosure. As illustrated, the GUI 154 includes an alert message 156 providing, in this example, the pseudonym of the user 20-1, the active interest of the user 20-1, and a question as to whether the user 20-N desires to be introduced to the user 20-1. The GUI 154 also includes a check box 158 that, when selected, enables the user 20-N to define or otherwise select a pseudonym to be used when responding to the two-way beacon. In this example, the user 20-N is enabled to define a pseudonym via a text field 160. Lastly, the GUI 154 includes an Ignore button 162 and a Yes button 164. The Ignore button 162, if selected, enables the user 20-N to ignore the two-way beacon. The Yes button 164, if selected, enables the user 20-N to respond to the two-way beacon.

Returning to FIG. 12, once the user 20-N has chosen to respond to the two-way beacon, the mobile device 18-N, and more particularly the MAP application 32-N of the mobile device 18-N, sends a response to the MAP server 12 (step 1408). The response indicates that the user 20-N has chosen to respond to the two-way beacon narrowcast for the user 20-1 of the mobile device 18-1. Upon receiving the response, the social connection manager 62 of the MAP server 12 generates and sends a secret (e.g., a password) to the mobile device 18-N of the user 20-N (step 1410). The MAP application 32-N of the mobile device 18-N then presents the secret to the user 20-N (step 1412). In addition, the social connection manager 62 of the MAP server 12 sends a request for the secret, which is referred to herein as a secret request, to the mobile device 18-1 of the user 20-1 (step 1414). The MAP application 32-1 of the mobile device 18-1 then presents the secret request to the user 20-1 (step 1416).

At this point, the user 20-N shares the secret with the user 20-1 via out-of-band communication (step 1418). The out-of-band communication may be, for example, verbal communication between the users 20-1 and 20-N, Near Field Communication (NFC), or other type of communication that requires the users 20-1 and 20-N to be proximate to one another. Preferably, the out-of-band communication is such that it requires a face-to-face meeting between the users 20-1 and 20-N. Once the user 20-1 has received the secret from the user 20-N via out-of-band communication, the user 20-1 enters the secret at the mobile device 18-1. The MAP application 32-1 of the mobile device 18-1 receives the secret from the user 20-1 (step 1420) and then sends the secret to the MAP server 12 (step 1422). At this point, once the MAP server 12 receives the secret from the user 20-1, the MAP server 12 knows that the users 20-1 and 20-N have confirmed that they desire a new two-way social connection between them. As such, the social connection manager 62 of the MAP server 12 then adds a new two-way social connection between the users 20-1 and 20-N in one or more social networks maintained by the one or more social networking services 14 (step 1424). In one embodiment, the user 20-1 and/or the user 20-N is enabled to select or otherwise identify the particular social network to which the two-way social connection is to be added.

FIG. 15 illustrates an exemplary GUI 166 provided by the MAP application 32-N of the mobile device 18-N to present the secret to the user 20-N in step 1412 according to an exemplary embodiment of the present disclosure. As illustrated, the GUI 166 includes a message 168 including the secret and instructions to share the secret with the user 20-1. In addition, in this example, the GUI 166 includes a check box 170 that, if selected, results in the new two-way social connection between the users 20-1 and 20-N being added to the designated social networking service 14, which in this example is the LinkedIN® social networking service, upon being formalized, or confirmed, via the sharing of the secret with the user 20-1. Lastly, the GUI 166 includes a Cancel button 172 and a Continue button 174. The Cancel button 172, if selected, enables the user 20-N to refuse a social connection with the user 20-1 by stopping the process. The Continue button 174, if selected, enables the user 20-N to continue the process of adding the new two-way social connection between the users 20-1 and 20-N.

FIG. 16 illustrates an exemplary GUI 176 provided by the MAP application 32-1 of the mobile device 18-1 to present the secret request to the user 20-1 in step 1414 according to an exemplary embodiment of the present disclosure. As illustrated, the GUI 176 includes a message 178 including, in this example, the pseudonym of the user 20-N that has responded to the two-way beacon and a request for the user 20-1 to enter the secret in text field 180 to formalize, or confirm, the new two-way social connection between the users 20-1 and 20-N. In this example, the GUI 176 also includes a check box 182 that, if selected, results in the new two-way social connection between the users 20-1 and 20-N being added to the designated social networking service 14, which in this example is the LinkedIN® social networking service, upon entry of the secret in the text field 180. Lastly, the GUI 176 includes a Cancel button 184 and a Continue button 186. The Cancel button 184, if selected, enables the user 20-1 to refuse a social connection with the user 20-N by stopping the process. The Continue button 186, if selected, enables the user 20-1 to continue the process of adding the new two-way social connection between the users 20-1 and 20-N.

FIG. 17 illustrates the operation of the MAP server 12 to create new two-way social connections between the users 20-1 through 20-N in more detail according to one embodiment of the present disclosure. This process is a more detailed version of the operation of the MAP server 12 discussed above with respect to FIG. 12. First, as discussed above, the social connection manager 62 of the MAP server 12 receives a two-way beacon request from an initiating user, which is also referred to herein as an initiator (step 1500). In the example of FIG. 12, the user 20-1 is the initiator. In one embodiment, the two-way beacon request is initiated by the initiator at the mobile device 18 of the initiator and sent to the MAP server 12 by the mobile device 18 of the initiator in the manner described above. However, the present disclosure is not limited thereto. The two-way beacon request includes one or more configurations, or settings, including an active interest of the initiator and, optionally, a pseudonym to be used in lieu of the name, username, or other identifying information of the initiator.

Next, the social connection manager 62 of the MAP server 12 obtains an aggregate profile for a current crowd of the initiator (step 1502). The current crowd of the initiator is the crowd in which the initiator is currently located. More specifically, in one embodiment, the current crowd in which the initiator is located may be identified by the crowd analyzer 58 via the spatial crowd formation process of FIG. 6 performed for a geographic region encompassing the current location of the initiator. Alternatively, the crowd analyzer 58 may proactively perform the spatial crowd formation process of FIGS. 8A through 8D such that data defining the current crowd in which the initiator is currently located is proactively stored in the datastore 66 of the MAP server 12. In this case, the current crowd of the initiator may be identified by querying the datastore 66 of the MAP server 12. As discussed below, in one embodiment, the aggregate profile of the current crowd is generated by comparing the active interest of the initiator to the user profiles of the other users in the current crowd of the initiator to determine, for example, a number of user matches for the active interest in the current crowd or a ratio of the number of user matches for the active interest in the current crowd to a total number of users in the current crowd. Again, for purposes of generating the aggregate profile, the total number of users in the current crowd of the initiator may be the number of users in the current crowd other than the initiator.

The social connection manager 62 then determines whether the current crowd matches the active interest of the initiator based on the aggregate profile of the current crowd of the initiator (step 1504). In one embodiment, the aggregate profile of the current crowd includes a number of user matches for the active interest, and the current crowd is determined to match the active interest if the number of user matches for the active interest is greater than a predefined threshold number of user matches. The predefined threshold number of user matches may be configurable by the initiator or may be system-defined. In another embodiment, the aggregate profile of the current crowd includes a ratio of the number of user matches for the active interest to the total number of users in the current crowd, and the current crowd is determined to match the active interest if the ratio is greater than a predefined threshold ratio. The predefined threshold ratio may be configurable by the initiator or may be system-defined.

If the current crowd does not match the active interest, the process returns to step 1502 and is repeated. If the current crowd matches the active interest, the social connection manager 62 then narrowcasts a two-way beacon on behalf of the initiator (step 1506). The two-way beacon identifies the active interest of the initiator. In addition, the two-way beacon may include either the name, username, or other identifying information of the initiator or the pseudonym of the initiator. In one embodiment, the two-way beacon is narrowcast to the mobile devices 18 of all of the other users 20 in the current crowd of the initiator. In another embodiment, the two-way beacon is narrowcast to the mobile devices 18 of only those other users 20 in the current crowd of the initiator having user profiles that include interests that match the active interest.

Next, the social connection manager 62 determines whether a response to the two-way beacon has been received (step 1508). If not, the process proceeds to step 1512. If a response to the two-way beacon has been received from a responding user, or responder, the social connection manager 62 triggers a new two-way social connection process for the initiator and the responder (step 1510). The details of this process are discussed below with respect to FIG. 18. In general, the new two-way social connection process adds a two-way social connection between the initiator and the responder in one or more social networks maintained by one or more of the social networking services 14.

At this point, whether proceeding from step 1508 or 1510, the social connection manager 62 determines whether it is time to obtain a new aggregate profile for the initiator (step 1512). In one embodiment, a user-defined or system-defined time period defines a minimum amount of time between narrowcasting of successive two-way beacons for the initiator. For example, the time period may be five minutes. If the time period has not expired since narrowcasting the two-way beacon in step 1506, the process returns to step 1508. In this manner, after narrowcasting the two-way beacon, the social connection manager 62 waits for responses to the two-way beacon for an amount of time corresponding to the defined time period. Once the defined time period has expired, the process returns to step 1502 and is repeated. Note that by returning to step 1502 rather than step 1506, the social connection manager 62 also updates the aggregate profile of the current crowd of the initiator over time. This is beneficial because users may enter and leave the current crowd, which would result in a change in the aggregate profile of the current crowd, and because the initiator may join a new crowd. Also note that while in this embodiment the time interval for narrowcasting the two-way beacon and the time interval for updating the aggregate profile are the same, the present disclosure is not limited thereto. In an alternative embodiment, the time period used for updating the aggregate profile of the current crowd may be greater than the time period for narrowcasting the two-way beacon. For example, the two-way beacon may be narrowcast at five minute intervals whereas the aggregate profile may be updated at fifteen minute intervals.

FIG. 18 illustrates the process triggered in step 1510 of FIG. 17 in more detail according to one embodiment of the present disclosure. Upon receiving the response to the two-way beacon from the responder in step 1508 of FIG. 17, the social connection manager 62 triggers a new two-way social connection process for the initiator and the responder. This process begins by the social connection manager 62 generating and sending a secret (e.g., a password) to the responder (step 1600). More specifically, the social connection manager 62 sends the secret to the mobile device 18 of the responder where the secret is presented to the responder. As discussed above with respect to FIG. 12, the responder then shares the secret with the initiator via out-of-band communication. Upon receiving the secret from the responder, the initiator enters the secret at the mobile device 18 of the initiator, which then sends the secret to the social connection manager 62 of the MAP server 12.

The social connection manager 62 then determines whether the secret has been received from the initiator (step 1602). More specifically, in one embodiment, the social connection manager 62 determines whether the secret has been received from the initiator within a predefined time-out period. The time-out period may be system-defined or may be user-configurable. As an example, the time-out period may be five minutes. If the secret is not received from the initiator within the predefined time-out period, then the process ends such that a new two-way social connection between the initiator and the responder is not added. If the secret is received from the initiator, the social connection manager 62 adds a new two-way social connection between the initiator and the responder in one or more of the social networks maintained by one or more of the social networking services 14 (step 1604). The new two-way social connection indicates that the initiator knows the responder and the responder knows the initiator. The social connection manager 62 may add the new two-way social connection by communicating with the corresponding social networking service(s) 14 via, for example, an API. Once the new two-way social connection is added, the process ends.

FIG. 19 illustrates the operation of the system 10 of FIG. 1 to create new social connections between the users 20-1 through 20-N according to another embodiment of the present disclosure. First, the mobile device 18-1 sends a one-way beacon request to the MAP server 12 (step 1700). More specifically, in one embodiment, the MAP application 32-1 enables the user 20-1 to input a number of one-way beacon configurations, or settings. The one-way beacon configurations include one or more active interests of the user 20-1. The active interests are preferably one or more interests from the user profile of the user 20-1, but are not limited thereto. In addition, the one-way beacon configurations may include a pseudonym to be used in lieu of the actual name, username, or other identifying data of the user 20-1 when narrowcasting the one-way beacon, as discussed below. However, for the one-way beacon a pseudonym may not be desired. For example, if the user 20-1 is a famous or somewhat well-known person, the user 20-1 may desire to use his or her real name rather than a pseudonym. Once the user 20-1 inputs the one-way beacon configurations, the user 20-1 initiates sending of the one-way beacon request, and, in response, the MAP application 32-1 sends the one-way beacon request including the one-way beacon configurations to the MAP server 12. Referring back to FIG. 13, in the exemplary GUI 134, the user 20-1 may be enabled to define the configurations for the one-way beacon request by selecting the radio button 136 to enable the social connection creation process, defining a pseudonym if desired, defining the active interest for the one-way beacon in the field 144, and selecting the one-way radio button 148. The user 20-1 may then initiate the one-way beacon request by selecting the OK button 150.

Returning to FIG. 19, in response to receiving the one-way beacon request, the social connection manager 62 of the MAP server 12 detects when a current crowd of the user 20-1 matches the active interest of the user 20-1, which is included in the one-way beacon configurations (step 1702). More specifically, in one embodiment, social connection manager 62 periodically obtains an aggregate profile of a current crowd in which the user 20-1 is located. The current crowd in which the user 20-1 is located may be identified by the crowd analyzer 58 by periodically performing the spatial crowd formation process of FIG. 6 for a geographic region encompassing the current location of the user 20-1. Alternatively, the crowd analyzer 58 may proactively perform the spatial crowd formation process of FIGS. 8A through 8D such that the current crowd of the user 20-1 can be identified by querying the datastore 66 of the MAP server 12. As discussed below, in one embodiment, the aggregate profile of the current crowd is generated by comparing the active interest of the user 20-1 to the user profiles of the other users in the current crowd of the user 20-1. The aggregate profile of the current crowd preferably includes a number of user matches for the active interest in the current crowd or a ratio of the number of user matches for the active interest to a total number of users in the current crowd. For purposes of generating the aggregate profile, the total number of users in the current crowd of the user 20-1 may be the number of users in the current crowd other than the user 20-1. The social connection manager 62 then determines whether the current crowd matches the active interest of the user 20-1 based on the aggregate profile of the current crowd. For example, in one embodiment, there is a match if the number of user matches or the ratio of the number of user matches to the total number of users in the current crowd is greater than a predefined threshold. The predefined threshold may be configurable by the user 20-1 or may be system-defined.

In response to detecting there is a match between the current crowd of the user 20-1 and the active interest of the user 20-1, the social connection manager 62 of the MAP server 12 narrowcasts a one-way beacon to at least a subset of the current crowd of the user 20-1 (step 1704). In one embodiment, the social connection manager 62 narrowcasts the one-way beacon to all of the other users in the current crowd of the user 20-1. In another embodiment, the social connection manager 62 narrowcasts the one-way beacon to only those other users in the current crowd of the user 20-1 having user profiles that include interests that match the active interest of the user 20-1. Whether the one-way beacon is narrowcast to all of the other users in the current crowd of the user 20-1 or only to those other users in the current crowd of the user 20-1 having user profiles that include interests that match the active interest of the user 20-1, the one-way beacon is not narrowcast or otherwise sent to users outside of the current crowd of the user 20-1.

In this example, the user 20-N of the mobile device 18-N is in the current crowd of the user 20-1, and the one-way beacon is narrowcast to the mobile device 18-N of the user 20-N. Note that the one-way beacon is also narrowcast to the mobile devices 18 of other users 20 in the current crowd of the user 20-1. However, only the mobile device 18-N is illustrated for clarity and ease of discussion. The one-way beacon may be narrowcast using any suitable technology. In this embodiment, the one-way beacon is narrowcast to the mobile device 18-N via a dedicated communication session or link between the MAP server 12 and the MAP application 32-N of the mobile device 18-N over the network 28. However, other techniques for narrowcasting the one-way beacon may be used (e.g., SMS or MMS message). In response to receiving the one-way beacon, the mobile device 18-N presents an alert corresponding to the one-way beacon to the user 20-N (step 1706). In one embodiment, the alert is presented via the MAP application 32-N. The alert may ask the user 20-N if he or she would like to add a one-way, or tentative, social connection to the user 20-1. The one-way, or tentative, social connection is such that the user 20-N knows who the user 20-1 is, but the user 20-1 does not know who the user 20-N is until a two-way social connection is recommended, if ever. This mirrors asymmetric relationships in the real world where, for example, a person may know of Steve Jobs by attending MacWorld conferences, but Steve Jobs does not know of that person.

Once the user 20-N has chosen to respond to the one-way beacon, the mobile device 18-N, and more particularly the MAP application 32-N of the mobile device 18-N, sends a response to the MAP server 12 (step 1708). The response indicates that the user 20-N has chosen to respond to the one-way beacon narrowcast for the user 20-1 of the mobile device 18-1. In this embodiment, upon receiving the response, the social connection manager 62 of the MAP server 12 adds a tentative, or one-way, social connection between the users 20-1 and 20-N (step 1710). The tentative social connection may also be referred to as a one-way social connection from the user 20-N to the user 20-1. Preferably, the tentative social connection is stored at the MAP server 12 and is not provided to the social networking service(s) 14 at this point. In one embodiment, the tentative social connection is stored as a record or similar data structure that includes the user identifier of the user 20-1 for which the tentative social connection was created and either a user identifier or obfuscated (e.g., encrypted) user identifier of the user 20-N. In addition, the record for the tentative social connection may include a date and/or time at which the tentative social connection was created, information identifying a geographic location for the tentative social connection, or both. The geographic location for the tentative social connection may be the location of the user 20-1 at the time the tentative social connection was created, the location of the user 20-N at the time the tentative social connection was created, or a combination of the locations of the users 20-1 and 20-N at the time the tentative social connection was created.

In this embodiment, the social connection manager 62 of the MAP server 12 then analyzes the new tentative social connection between the users 20-1 and 20-N and one or more previously created tentative social connections between the users 20-1 and 20-N to determine whether to recommend a two-way social connection between the users 20-1 and 20-N (step 1712). In one embodiment, a two-way social connection is recommended if more than a predefined threshold number of tentative social connections between the users 20-1 and 20-N have been created. In another embodiment, a two-way social connection is recommended if more than a predefined threshold number of tentative social connections between the users 20-1 and 20-N have been created during a desired time window. The desired time window may be, for example, a time window relative to the current time (e.g., past week, past month, past 90 days, or the like). In yet another embodiment, a two-way social connection is recommended if more than a predefined threshold number of tentative social connections between the users 20-1 and 20-N have been created at the same geographic location or within the same geographic area (e.g., within a predefined maximum distance from one another). In yet another embodiment, a two-way social connection is recommended if more than a predefined threshold number of tentative social connections between the users 20-1 and 20-N have been created for the same geographic location or the same geographic area during a desired time window.

In this example, the social connection manager 62 determines that a two-way social connection is to be recommended. As such, the social connection manager 62 sends an alert to the mobile device 18-1 of the user 20-1 (step 1714). The alert notifies the user 20-1 that a two-way social connection with the user 20-N is recommended and enables the user 20-1 to accept the recommendation. At the mobile device 18-1, upon receiving the alert, the MAP application 32-1 presents the alert to the user 20-1 (step 1716). FIG. 20 illustrates an exemplary GUI 188 for presenting the alert to the user 20-1. As illustrated, in this example, the alert includes a message 190 that notifies the user 20-1 that a two-way social connection has been recommended with another user. In this example, the identity of the other user is not revealed. Alternatively, the name, user name, or other user identifier of the user 20-N or the pseudonym of the user 20-N may be included in the message 190. The GUI 188 also includes an Ignore button 192 and a Yes button 194. The Ignore button 192, if selected, enables the user 20-1 to ignore the recommendation. The Yes button 194, if selected, enables the user 20-1 to accept the recommendation.

Returning to FIG. 19, if the user 20-1 accepts the recommendation, a corresponding response is sent to the MAP server 12 (step 1718). Upon receiving the response, the social connection manager 62 generates and sends a secret (e.g., a password) to the mobile device 18-N of the user 20-N (step 1720). The MAP application 32-N of the mobile device 18-N then presents the secret to the user 20-N (step 1722). In addition, the social connection manager 62 of the MAP server 12 sends a request for the secret, which is referred to herein as a secret request, to the mobile device 18-1 of the user 20-1 (step 1724). The MAP application 32-1 of the mobile device 18-1 then presents the secret request to the user 20-1 (step 1726).

At this point, the user 20-N shares the secret with the user 20-1 via out-of-band communication (step 1728). The out-of-band communication may be, for example, verbal communication between the users 20-1 and 20-N, NFC, or other type of communication that requires the users 20-1 and 20-N to be proximate to one another. Preferably, the out-of-band communication is such that it requires a face-to-face meeting between the users 20-1 and 20-N. Once the user 20-1 has received the secret from the user 20-N via out-of-band communication, the user 20-1 enters the secret at the mobile device 18-1. The MAP application 32-1 of the mobile device 18-1 receives the secret from the user 20-1 (step 1730) and then sends the secret to the MAP server 12 (step 1732). At this point, once the MAP server 12 receives the secret from the user 20-1, the MAP server 12 knows that the users 20-1 and 20-N have confirmed that they desire a new two-way social connection between them. As such, the social connection manager 62 of the MAP server 12 then adds a new two-way social connection between the users 20-1 and 20-N in one or more social networks maintained by the one or more social networking services 14 (step 1734). In one embodiment, the user 20-1 and/or the user 20-N is enabled to select or otherwise identify the particular social network to which the two-way social connection is to be added.

FIG. 21 illustrates the operation of the MAP server 12 to create new social connections between the users 20-1 through 20-N in more detail according to another embodiment of the present disclosure. This process is a more detailed version of the operation of the MAP server 12 discussed above with respect to FIG. 19. First, as discussed above, the social connection manager 62 of the MAP server 12 receives a one-way beacon request from an initiating user, which is also referred to herein as an initiator (step 1800). In the example of FIG. 19, the user 20-1 is the initiator. In one embodiment, the one-way beacon request is initiated by the initiator at the mobile device 18 of the initiator and sent to the MAP server 12 by the mobile device 18 of the initiator in the manner described above. However, the present disclosure is not limited thereto. The one-way beacon request includes one or more configurations, or settings, including an active interest of the initiator and, optionally, a pseudonym to be used in lieu of the name, username, or other identifying information of the initiator.

Next, the social connection manager 62 of the MAP server 12 obtains an aggregate profile for a current crowd of the initiator (step 1802). The current crowd of the initiator is the crowd in which the initiator is currently located. More specifically, in one embodiment, the current crowd in which the initiator is located may be identified by the crowd analyzer 58 via the spatial crowd formation process of FIG. 6 performed for a geographic region encompassing the current location of the initiator. Alternatively, the crowd analyzer 58 may proactively perform the spatial crowd formation process of FIGS. 8A through 8D such that data defining the current crowd in which the initiator is currently located is proactively stored in the datastore 66 of the MAP server 12. In this case, the current crowd of the initiator may be identified by querying the datastore 66 of the MAP server 12. As discussed below, in one embodiment, the aggregate profile of the current crowd is generated by comparing the active interest of the initiator to the user profiles of the other users in the current crowd of the initiator to determine, for example, a number of user matches for the active interest in the current crowd or a ratio of the number of user matches for the active interest to a total number of users in the current crowd. Again, for purposes of generating the aggregate profile, the total number of users in the current crowd of the initiator may be the number of users in the current crowd other than the initiator.

The social connection manager 62 then determines whether the current crowd matches the active interest of the initiator based on the aggregate profile of the current crowd of the initiator (step 1804). In one embodiment, the aggregate profile of the current crowd includes a number of user matches for the active interest, and the current crowd is determined to match the active interest if the number of user matches for the active interest is greater than a predefined threshold number of user matches. The predefined threshold number of user matches may be configurable by the initiator or may be system-defined. In another embodiment, the aggregate profile of the current crowd includes a ratio of the number of user matches for the active interest to the total number of users in the current crowd, and the current crowd is determined to match the active interest if the ratio is greater than a predefined threshold ratio. The predefined threshold ratio may be configurable by the initiator or may be system-defined.

If the current crowd does not match the active interest, the process returns to step 1802 and is repeated. If the current crowd matches the active interest, the social connection manager 62 then narrowcasts a one-way beacon on behalf of the initiator (step 1806). The one-way beacon identifies the active interest of the initiator. In addition, the one-way beacon may include either the name, username, or other identifying information of the initiator or the pseudonym of the initiator. In one embodiment, the one-way beacon is narrowcast to the mobile devices 18 of all of the other users 20 in the current crowd of the initiator. In another embodiment, the one-way beacon is narrowcast to the mobile devices 18 of only those other users 20 in the current crowd of the initiator having user profiles that include interests that match the active interest.

Next, the social connection manager 62 determines whether a response to the one-way beacon has been received (step 1808). If not, the process proceeds to step 1812. If a response to the one-way beacon has been received from a responding user, or responder, the social connection manager 62 triggers a new tentative social connection process for the initiator and the responder (step 1810). The details of this process are discussed below with respect to FIG. 22. In general, the new tentative social connection process adds a tentative social connection between the initiator and the responder and, if appropriate, adds a two-way social connection between the initiator and the responder in one or more of the social networks maintained by the one or more social networking services 14.

At this point, whether proceeding from step 1808 or 1810, the social connection manager 62 determines whether it is time to obtain a new aggregate profile for the initiator (step 1812). In one embodiment, a user-defined or system-defined time period defines a minimum amount of time between narrowcasting of successive one-way beacons for the initiator. For example, the time period may be five minutes. If the time period has not expired since narrowcasting the one-way beacon in step 1806, the process returns to step 1808. In this manner, after narrowcasting the one-way beacon, the social connection manager 62 waits for responses to the one-way beacon for an amount of time corresponding to the defined time period. Once the defined time period has expired, the process returns to step 1802 and is repeated. Note that by returning to step 1802 rather than step 1806, the social connection manager 62 also updates the aggregate profile of the current crowd of the initiator over time. This is beneficial because users may enter and leave the current crowd, which would result in a change in the aggregate profile of the current crowd, and because the initiator may join a new crowd. Also note that while in this embodiment the time interval for narrowcasting the one-way beacon and the time interval for updating the aggregate profile are the same, the present disclosure is not limited thereto. In an alternative embodiment, the time period used for updating the aggregate profile of the current crowd may be greater than the time period for narrowcasting the one-way beacon. For example, the one-way beacon may be narrowcast at five minute intervals whereas the aggregate profile may be updated at fifteen minute intervals.

FIG. 22 illustrates the processes triggered in step 1810 of FIG. 21 in more detail according to one embodiment of the present disclosure. Upon receiving the response to the one-way beacon from the responder in step 1808 of FIG. 21, the social connection manager 62 triggers a new tentative social connection process for the initiator and the responder. This process begins by the social connection manager 62 adding a new tentative social connection between the initiator and the responder (step 1900). Next, the social connection manager 62 determines whether previous tentative social connections between the initiator and the responder have been created and stored (step 1902). If not, the process ends. Otherwise, the social connection manager 62 determines whether to recommend a two-way social connection between the initiator and the responder based on the tentative social connections created between the initiator and the responder (step 1904). As discussed above, in one embodiment, a two-way social connection is recommended if more than a predefined threshold number of tentative social connections between the users 20-1 and 20-N have been created and stored. In another embodiment, a two-way social connection is recommended if more than a predefined threshold number of tentative social connections between the users 20-1 and 20-N have been created and stored during a desired time window. The desired time window may be, for example, a time window relative to the current time (e.g., past week, past month, past 90 days, or the like). In yet another embodiment, a two-way social connection is recommended if more than a predefined threshold number of tentative social connections between the users 20-1 and 20-N have been created at the same geographic location or within the same geographic area (e.g., within a predefined maximum distance from one another). In yet another embodiment, a two-way social connection is recommended if more than a predefined threshold number of tentative social connections between the users 20-1 and 20-N have been created for the same geographic location or the same geographic area during a desired time window.

If the social connection manager 62 determines that a two-way social connection is not to be recommended, the process ends. Otherwise, the social connection manager 62 sends an alert to the initiator that includes a recommendation to add a new two-way social connection (step 1906). The social connection manager 62 then receives a response from the initiator that, in this example, gives approval to add the recommended two-way social connection (step 1908). Next, the social connection manager 62 generates and sends a secret (e.g., a password) to the responder (step 1910). More specifically, the social connection manager 62 sends the secret to the mobile device 18 of the responder where the secret is presented to the responder. As discussed above with respect to FIG. 19, the responder then shares the secret with the initiator via out-of-band communication. Upon receiving the secret from the responder, the initiator enters the secret at the mobile device 18 of the initiator, which then sends the secret to the social connection manager 62 of the MAP server 12.

The social connection manager 62 then determines whether the secret has been received from the initiator (step 1912). More specifically, in one embodiment, the social connection manager 62 determines whether the secret has been received from the initiator within a predefined time-out period. The time-out period may be system-defined or user-configurable. As an example, the time-out period may be five minutes. If the secret is not received from the initiator within the predefined time-out period, then the process ends such that a new two-way social connection between the initiator and the responder is not added. If the secret is received from the initiator, the social connection manager 62 adds a new two-way social connection between the initiator and the responder in one or more of the social networks maintained by one or more of the social networking services 14 (step 1914). The social connection manager 62 may add the new two-way social connection by communicating with the corresponding social networking service(s) 14 via, for example, an API. Once the new social connection is added, the process ends.

FIG. 23 illustrates a process for obtaining the aggregate profile for the current crowd of the initiator of a beacon request according to one embodiment of the present disclosure. Here, the initiator may be the initiator of a two-way beacon request or a one-way beacon request. After the current crowd of the initiator has been identified, the aggregation engine 60 selects the next user in the current crowd (step 2000). For the first iteration, the next user is the first user in the current crowd. Next, the aggregation engine 60 compares the user profile of the user in the current crowd to the active interest of the initiator of the beacon request (step 2002). The comparison determines whether there is an interest in the user profile of the user in the current crowd that matches the active interest of the initiator.

Next, the aggregation engine 60 determines whether there are more users in the current crowd (step 2004). If so, the process returns to step 2000 and is repeated for the next user in the current crowd. Once all of the users in the current crowd have been processed, the aggregation engine 60 generates an aggregate profile for the current crowd (step 2006). In this embodiment, the aggregate profile includes the number of user matches for the active interest in the current crowd (i.e., the number of users in the current crowd having user profiles that include interests that match the active interest), a ratio of the number of user matches for the active interest in the current crowd over a total number of users in the current crowd, or both.

FIG. 24 is a block diagram of the MAP server 12 according to one embodiment of the present disclosure. As illustrated, the MAP server 12 includes a controller 196 connected to memory 198, one or more secondary storage devices 200, and a communication interface 202 by a bus 204 or similar mechanism. The controller 196 is a microprocessor, digital Application Specific Integrated Circuit (ASIC), Field Programmable Gate Array (FPGA), or the like. In this embodiment, the controller 196 is a microprocessor, and the application layer 40, the business logic layer 42, and the object mapping layer 64 (FIG. 2) are implemented in software and stored in the memory 198 for execution by the controller 196. Further, the datastore 66 (FIG. 2) may be implemented in the one or more secondary storage devices 200. The secondary storage devices 200 are digital data storage devices such as, for example, one or more hard disk drives. The communication interface 202 is a wired or wireless communication interface that communicatively couples the MAP server 12 to the network 28 (FIG. 1). For example, the communication interface 202 may be an Ethernet interface, local wireless interface such as a wireless interface operating according to one of the suite of IEEE 802.11 standards, or the like.

FIG. 25 is a block diagram of the mobile device 18-1 according to one embodiment of the present disclosure. This discussion is equally applicable to the other mobile devices 18-2 through 18-N. As illustrated, the mobile device 18-1 includes a controller 206 connected to memory 208, a communication interface 210, one or more user interface components 212, and the location function 36-1 by a bus 214 or similar mechanism. The controller 206 is a microprocessor, digital ASIC, FPGA, or the like. In this embodiment, the controller 206 is a microprocessor, and the MAP client 30-1, the MAP application 32-1, and the third-party applications 34-1 are implemented in software and stored in the memory 208 for execution by the controller 206. In this embodiment, the location function 36-1 is a hardware component such as, for example, a GPS receiver. The communication interface 210 is a wireless communication interface that communicatively couples the mobile device 18-1 to the network 28 (FIG. 1). For example, the communication interface 210 may be a local wireless interface such as a wireless interface operating according to one of the suite of IEEE 802.11 standards, a mobile communications interface such as a cellular telecommunications interface, or the like. The one or more user interface components 212 include, for example, a touchscreen, a display, one or more user input components (e.g., a keypad), a speaker, or the like, or any combination thereof.

FIG. 26 is a block diagram of a server 216 that operates to host one of the social networking services 14 according to one embodiment of the present disclosure. As illustrated, the server 216 includes a controller 218 connected to memory 220, one or more secondary storage devices 222, a communication interface 224, and one or more user interface components 226 by a bus 228 or similar mechanism. The controller 218 is a microprocessor, digital ASIC, FPGA, or the like. In this embodiment, the controller 218 is a microprocessor, and the social networking service 14 (FIG. 1) is implemented in software and stored in the memory 220 for execution by the controller 218. The one or more secondary storage devices 222 are digital storage devices such as, for example, one or more hard disk drives. The communication interface 224 is a wired or wireless communication interface that communicatively couples the server 216 to the network 28 (FIG. 1). For example, the communication interface 224 may be an Ethernet interface, local wireless interface such as a wireless interface operating according to one of the suite of IEEE 802.11 standards, or the like. The one or more user interface components 226 include, for example, a touchscreen, a display, one or more user input components (e.g., a keypad), a speaker, or the like, or any combination thereof.

FIG. 27 is a block diagram of a computing device 230 that operates to host the third-party service 26 according to one embodiment of the present disclosure. The computing device 230 may be, for example, a physical server, but is not limited thereto. As illustrated, the computing device 230 includes a controller 232 connected to memory 234, one or more secondary storage devices 236, a communication interface 238, and one or more user interface components 240 by a bus 242 or similar mechanism. The controller 232 is a microprocessor, digital ASIC, FPGA, or the like. In this embodiment, the controller 232 is a microprocessor, and the social networking service 14 is implemented in software and stored in the memory 234 for execution by the controller 232. The one or more secondary storage devices 236 are digital storage devices such as, for example, one or more hard disk drives. The communication interface 238 is a wired or wireless communication interface that communicatively couples the computing device 230 to the network 28 (FIG. 1). For example, the communication interface 238 may be an Ethernet interface, local wireless interface such as a wireless interface operating according to one of the suite of IEEE 802.11 standards, a mobile communications interface such as a cellular telecommunications interface, or the like. The one or more user interface components 240 include, for example, a touchscreen, a display, one or more user input components (e.g., a keypad), a speaker, or the like, or any combination thereof.

Those skilled in the art will recognize improvements and modifications to the preferred embodiments of the present invention. All such improvements and modifications are considered within the scope of the concepts disclosed herein and the claims that follow.

What is claimed is:

Claims

1. A computer-implemented method comprising:

detecting when a current crowd of a first user matches an active interest of the first user, the current crowd comprising the first user and a plurality of other users;

narrowcasting a beacon to mobile devices of at least a subset of the plurality of other users in response to detecting that the current crowd of the first user matches the active interest of the first user;

receiving a response to the beacon from a mobile device of a second user from the plurality of other users in the current crowd of the first user; and

creating a new social connection between the first and second users upon receiving the response to the beacon from the mobile device of the second user.

2. The method of claim 1 wherein narrowcasting the beacon comprises narrowcasting the beacon only to the mobile devices of the plurality of other users in the current crowd of the first user.

3. The method of claim 1 wherein narrowcasting the beacon comprises narrowcasting the beacon only to the mobile devices of a subset of the plurality of other users in the current crowd of the first user that have user profiles including interests that match the active interest of the first user.

4. The method of claim 1 wherein the beacon is a two-way beacon, and creating the new social connection comprises adding a new two-way social connection between the first and second users in a social network.

5. The method of claim 4 wherein the social network is maintained by a remotely hosted social networking service.

6. The method of claim 4 further comprising:

providing a secret to the mobile device of the second user such that the second user shares the secret with the first user via out-of-band communication; and

receiving the secret from a mobile device of the first user;

wherein creating the new social connection comprises creating the new social connection upon receiving the secret from the mobile device of the first user.

7. The method of claim 1 wherein the beacon is a one-way beacon, and creating the new social connection comprises adding a new tentative social connection between the first and second users.

8. The method of claim 7 further comprising making a determination as to whether to recommend a two-way social connection between the first and second users based on an analysis of the new tentative social connection between the first and second users and one or more additional tentative social connections between the first and second users that were previously added.

9. The method of claim 8 wherein making a determination as to whether to recommend a two-way social connection between the first and second users comprises making a determination to recommend a two-way social connection between the first and second users if a number of tentative social connections between the first and second users is greater than a predefined threshold number.

10. The method of claim 8 wherein making a determination as to whether to recommend a two-way social connection between the first and second users comprises making a determination to recommend a two-way social connection between the first and second users if a number of tentative social connections between the first and second users created during a defined time window is greater than a predefined threshold number.

11. The method of claim 8 wherein each tentative social connection of the new tentative social connection and the one or more additional tentative social connections is associated with a geographic location, and making a determination as to whether to recommend a two-way social connection between the first and second users comprises making a determination to recommend a two-way social connection between the first and second users if a number of tentative social connections between the first and second users associated with the same geographic location is greater than a predefined threshold number.

12. The method of claim 8 wherein each tentative social connection of the new tentative social connection and the one or more additional tentative social connections is associated with a geographic location, and making a determination as to whether to recommend a two-way social connection between the first and second users comprises making a determination to recommend a two-way social connection between the first and second users if a number of tentative social connections between the first and second users associated with the same geographic area is greater than a predefined threshold number.

13. The method of claim 8 wherein each tentative social connection of the new tentative social connection and the one or more additional tentative social connections is associated with a geographic location, and making a determination as to whether to recommend a two-way social connection between the first and second users comprises making a determination to recommend a two-way social connection between the first and second users if a number of tentative social connections between the first and second users, including the new tentative social connection and the one or more additional tentative social connections, created within a defined time window and associated with the same geographic location is greater than a predefined threshold number.

14. The method of claim 8 wherein each tentative social connection of the new tentative social connection and the one or more additional tentative social connections is associated with a geographic location, and making a determination as to whether to recommend a two-way social connection between the first and second users comprises making a determination to recommend a two-way social connection between the first and second users if a number of tentative social connections between the first and second users, including the new tentative social connection and the one or more additional tentative social connections, created within a defined time window and associated with the same geographic area is greater than a predefined threshold number.

15. The method of claim 8 further comprising providing an alert to the first user including a recommendation to add a two-way social connection between the first and second users if a determination is made to recommend a two-way social connection between the first and second users.

16. The method of claim 15 further comprising adding a new two-way social connection between the first and second users if the first user accepts the recommendation to add the two-way social connection between the first and second users.

17. The method of claim 16 further comprising, if the first user accepts the recommendation to add the two-way social connection between the first and second users:

providing a secret to the mobile device of the second user such that the second user shares the secret with the first user via out-of-band communication; and

receiving the secret from a mobile device of the first user;

wherein adding the new two-way social connection comprises adding the new two-way social connection between the first and second users upon receiving the secret from the mobile device of the first user.

18. The method of claim 1 wherein detecting when the current crowd of the first user matches the active interest of the first user comprises:

obtaining an aggregate profile of the current crowd of the first user; and

determining whether the current crowd matches the active interest based on the aggregate profile of the current crowd.

19. The method of claim 18 wherein:

obtaining the aggregate profile of the current crowd of the first user comprises comparing the active interest of the first user to user profiles of the plurality of other users in the current crowd to determine a number of user matches for the active interest in the current crowd of the first user; and

determining whether the current crowd matches the active interest based on the aggregate profile of the current crowd comprises making a determination that the current crowd of the first user matches the active interest of the first user if the number of user matches for the active interest in the current crowd is greater than a predefined threshold number of user matches.

20. The method of claim 18 wherein:

obtaining the aggregate profile of the current crowd of the first user comprises comparing the active interest of the first user to user profiles of the plurality of other users in the current crowd to determine a ratio of a number of user matches for the active interest in the current crowd of the first user over a number of users in the plurality of other users in the current crowd of the first user; and

determining whether the current crowd matches the active interest based on the aggregate profile of the current crowd comprises making a determination that the current crowd of the first user matches the active interest of the first user if the ratio is greater than a predefined threshold ratio.

21. The method of claim 1 further comprising forming the current crowd of the first user via a spatial crowd formation process.

22. A computer-readable medium storing software for instructing a controller of a computing device to:

detect when a current crowd of a first user matches an active interest of the first user, the current crowd comprising the first user and a plurality of other users;

narrowcast a beacon to mobile devices of at least a subset of the plurality of other users in response to detecting that the current crowd of the first user matches the active interest of the first user;

receive a response to the beacon from a mobile device of a second user from the plurality of other users in the current crowd of the first user; and

create a new social connection between the first and second users upon receiving the response to the beacon from the mobile device of the second user.

23. A computing system comprising:

a communication interface communicatively coupling the computing system to mobile devices via a network; and

a controller associated with the communication interface and adapted to: detect when a current crowd of a first user matches an active interest of the first user, the current crowd comprising the first user and a plurality of other users; narrowcast a beacon to mobile devices of at least a subset of the plurality of other users in response to detecting that the current crowd of the first user matches the active interest of the first user; receive a response to the beacon from a mobile device of a second user from the plurality of other users in the current crowd of the first user; and create a new social connection between the first and second users upon receiving the response to the beacon from the mobile device of the second user.