Abstract: Systems and methods are provided for filtering and/or creating Points-of-Interest (POIs). In one embodiment, a list of POIs is obtained and then filtered based on crowd data related to the list of POIs to provide a filtered list of POIs. In another embodiment, one or more crowd-sourced POIs are created based on one or more crowds relevant to a corresponding bounding region for POI creation.

Abstract: Systems and methods are provided for filtering and/or creating Points-of-Interest (POIs). In one embodiment, a list of POIs is obtained and then filtered based on crowd data related to the list of POIs to provide a filtered list of POIs. In another embodiment, one or more crowd-sourced POIs are created based on one or more crowds relevant to a corresponding bounding region for POI creation.

Abstract: Systems and methods are provided for filtering and/or creating Points-of-Interest (POIs). In one embodiment, a list of POIs is obtained and then filtered based on crowd data related to the list of POIs to provide a filtered list of POIs. In another embodiment, one or more crowd-sourced POIs are created based on one or more crowds relevant to a corresponding bounding region for POI creation.

Abstract: Systems and methods are provided for filtering and/or creating Points-of-Interest (POIs). In one embodiment, a list of POIs is obtained and then filtered based on crowd data related to the list of POIs to provide a filtered list of POIs. In another embodiment, one or more crowd-sourced POIs are created based on one or more crowds relevant to a corresponding bounding region for POI creation.

Abstract: Systems and methods are disclosed for obtaining secondary indications of locations of users for use by a location-based service. In one embodiment, a secondary indication of a location of one or more users is obtained from a source of secondary indications of locations of users. The secondary indication includes a location of the one or more users and timing information defining when the one or more users were or will be located at the location. The secondary indication of the location of the one or more users is then stored and utilized to provide the location-based service. In one embodiment, the secondary indication is utilized to store historical aggregate user profile data by location and/or to provide aggregate user profile data for crowds of users formed via a spatial crowd formation process.

Abstract: A system for a mobile device to provide access to a data collection, such as a user's data collection for example, without requiring either persistent storage of the complete data collection locally on the mobile device, or network access requests for each user data request from the mobile device. In an embodiment, the system employs a data probability function to predict the probability of the mobile device accessing specific types of user data based on the operating mode of the mobile device. The system executes as a background process to provide and store locally on the mobile device, the data most probable to be accessed at the mobile device. The data most likely to be accessed via the mobile device is available locally, thereby minimizing latency issues that occur when data requests cannot be fulfilled using data stored locally in the mobile device and network requests are performed.

Abstract: A system and method are provided for forming crowds of users and providing access to corresponding crowd data. In one embodiment, a central system, which includes one or more servers, operates to obtain current locations for users of mobile devices. The system forms a crowd including a number of users based on the current locations of the number of users using a spatial crowd formation process based on an optimal inclusion distance that is a function of density of users of the plurality of users within a bounding region. The central system then generates crowd data for the crowd and provides access to the crowd data for the crowd. In one embodiment, the crowd data for the crowd includes an aggregate profile for the crowd. In another embodiment, the crowd data includes data characterizing the crowd. The central system provides access to the crowd data by serving crowd data requests.

Abstract: A music diary processor for generating an electronic music diary. The music diary processor receives a plurality of event identifiers from a user, wherein each event identifier identifies a respective life event associated with the user. The user can also provide a date identifier identifying a date associated with the life event, a song identifier identifying one or more songs identified by the user as being associated with the live event. The event identifiers, song identifiers and the date identifiers are stored in an electronic storage medium wherein each song identifier and date identifier is coupled with at least one respective event identifier, and a plurality of event identifiers are coupled with each other. The music diary processor can serve as a music discovery vehicle, wherein the music diary processor can use data entered by a user to locate songs and other data associated with other music diaries.

Abstract: The claimed subject matter is directed to systems and methods for providing passive crowd-sourced alternate route recommendations. In one embodiment, locations of users of a number of mobile location-aware devices are tracked over time. Upon receiving a request, users of mobile location-aware devices that have traveled from a desired start location to a desired stop location are identified. At least one of the different routes taken by one or more users from the desired start location to the desired stop location is provided to the requestor as at least one recommended alternate route. The different routes taken by the one or more users from the desired start location to the desired stop location include routes taken that begin before the desired start location and go through the start location and routes taken that stop beyond the desired stop location and go through the desired stop location.

Abstract: Systems and methods are disclosed for distributing micro-blog posts to ad-hoc micro-blogging groups. In one embodiment, a micro-blog post of a user is obtained. A crowd in which the user is located is determined, where the crowd is a group of spatially proximate users. The micro-blog post of the user is tagged with a crowd identifier of the crowd in which the user is located such that the micro-blog post includes a crowd identifier tag. Publication of the micro-blog post including the crowd identifier tag is then effected.

Abstract: A system and method are provided for maintaining a historical record of anonymized user profile data for mobile device users and serving historical requests. In one embodiment, a central system, which includes one or more servers, operates to obtain current locations and user profiles for users of mobile devices. The central system processes the current locations and the user profiles of the users over time to maintain a historical record of anonymized user profile data by location. By anonymizing the user data, privacy of the users of the mobile devices is maintained. The central system may then use the historical record of anonymized user profile data to respond to historical requests. The historical requests may be made by users of the mobile devices, subscribers, and/or third-party services.

Abstract: The present disclosure relates to forming crowds of users taking into account known physical boundaries. In general, current locations of a number of users are obtained. A crowd of users is then formed based on the current locations of the users while taking into account one or more known physical boundaries such that the crowd does not include spatially proximate users on opposite sides of the one or more known physical boundaries. By utilizing known physical boundaries in a spatial crowd formation process, users that are spatially proximate to one another but are separated by a physical boundary are not included in the same crowd. In this manner, the spatial crowd formation process provides accurate and meaningful crowd formation in environments such as, but not limited to, buildings with multiple rooms, shopping malls, or the like. Crowd data representing users in the formed crowd is generated.

Abstract: Systems and methods are disclosed for distributing micro-blog posts to ad-hoc micro-blogging groups. In one embodiment, a micro-blog post of a user is obtained. A crowd in which the user is located is determined, where the crowd is a group of spatially proximate users. The micro-blog post of the user is tagged with a crowd identifier of the crowd in which the user is located such that the micro-blog post includes a crowd identifier tag. Publication of the micro-blog post including the crowd identifier tag is then effected.

Abstract: The present disclosure relates to forming crowds of users taking into account known physical boundaries. In general, current locations of a number of users are obtained. A crowd of users is then formed based on the current locations of the users while taking into account one or more known physical boundaries such that the crowd does not include spatially proximate users on opposite sides of the one or more known physical boundaries. By utilizing known physical boundaries in a spatial crowd formation process, users that are spatially proximate to one another but are separated by a physical boundary are not included in the same crowd. In this manner, the spatial crowd formation process provides accurate and meaningful crowd formation in environments such as, but not limited to, buildings with multiple rooms, shopping malls, or the like. Crowd data representing users in the formed crowd is generated.

Abstract: A system and method are provided for forming crowds of users and providing access to corresponding crowd data. In one embodiment, a central system, which includes one or more servers, operates to obtain current locations for users of mobile devices. The system forms a crowd including a number of users based on the current locations of the number of users using a spatial crowd formation process based on an optimal inclusion distance that is a function of density of users of the plurality of users within a bounding region. The central system then generates crowd data for the crowd and provides access to the crowd data for the crowd. In one embodiment, the crowd data for the crowd includes an aggregate profile for the crowd. In another embodiment, the crowd data includes data characterizing the crowd. The central system provides access to the crowd data by serving crowd data requests.

Abstract: Contiguous location based user networks are disclosed herein. A method includes receiving an identification of an area of interest associated with a user of, and transmitting the identification of the area of interest to a server. The method includes determining a location of the user device and transmitting the location to the server. The method includes receiving information identifying a proximity group comprising the user and a plurality of other users. The proximity group includes least one other user being within a proximate area of the location of the user device and having an area of interest corresponding to the area of interest of the user. The proximate area corresponds to a second geographic region smaller than the area of interest. The proximity group further comprising at least one additional other user identified as a neighbor of each of the user and the at least one other user.

Abstract: Systems and methods for providing passive crowd-sourced alternate route recommendations are disclosed. In one embodiment, locations of users of a number of mobile location-aware devices are tracked over time. Upon receiving a request, users of mobile location-aware devices that have traveled from a desired start location to a desired stop location are identified. At least one of the different routes taken by one or more users from the desired start location to the desired stop location is provided to the requestor as at least one recommended alternate route.

Abstract: Systems and methods are disclosed for distributing micro-blog posts to ad-hoc micro-blogging groups. In one embodiment, a micro-blog post of a user is obtained. A crowd in which the user is located is determined, where the crowd is a group of spatially proximate users. The micro-blog post of the user is tagged with a crowd identifier of the crowd in which the user is located such that the micro-blog post includes a crowd identifier tag. Publication of the micro-blog post including the crowd identifier tag is then effected.

Abstract: Systems and methods relating to a Media Collection Aggregation System (MCAS) are provided. In one embodiment, a number of nodes are connected over a Local Area Network (LAN) to provide an ad-hoc MCAS network. At least some of the nodes in the MCAS network share locally stored media collections, or select subsets thereof, with the other nodes in the MCAS network. Each node in the MCAS network selects and aggregates one or more of the shared media collections to provide an aggregate media collection for that node. One of the nodes in the MCAS network is a proxy node that provides a proxy service that enables remote participation in the MCAS network. In one embodiment, the proxy node enables one or more remote nodes to passively and/or actively participate in the MCAS network.

Abstract: A system and method of contextually filtering content presented to a user on a mobile device based on contextual tagging. The user controls how content will be filtered by the mobile device by creating contextual tags and associating or tagging content with the contextual tags. The contextual tag includes a contextual behavior that is either satisfied or not based on the current context of the mobile device. During operation, content accessible to the mobile device is searched to determine which contextual tags are met based on the current context of the mobile device. Content tagged with contextual tags whose behavior is currently met based on the current context of the mobile device are filtered and presented to the user. This allows the automatic presentation of a more manageable subgroup of content to the user on the mobile device based on the current context of the mobile device.