Activity-Based Relationship System

Abstract

A method of representing relationships among a plurality of entities based on analysis of on-line activity of the entities is provided. A computer system receives identity information for at least one entity for determining activity-based relationships. The computer system captures on-line activity data of the at least one entity. The computer system analyzes the activity data to identify other entities and subjects of interest. The computer system determines relationship activity metrics. The computer system presents, on a graphical display system based on the relationship activity metrics, the at least one entity, the other entities, and the subjects of interest as a set of nodes in an Activity-based connection diagram with relationship activity metrics. The computer system then presents, on a graphical display system based on the relationship activity metrics, connections among the nodes in the activity-based connection diagram.

Description

This application claims the benefit of U.S. Provisional Patent Application Ser. No. 62/029,910, filed Jul. 28, 2014, and entitled “Dynamic User Interface.”

BACKGROUND INFORMATION

1. Field

The present disclosure relates generally to an improved data processing system. In particular, the present disclosure relates to a method and apparatus for identifying and displaying employee connections in an organization based on monitored on-line activities. Still more particularly, the present disclosure relates to a method and apparatus for a graphic user interface used in identifying and displaying employee connections in an organization to facilitate a desired level of interaction therefore.

2. Background

Information systems are used for many different purposes. For example, an information system may be used to provide communication between, and distribute ideas amongst employees within an organization. Businesses rely on collaborative efforts facilitated by this communication to achieve the organizational goals of the business.

However, the information organization methods and systems that are currently used to facilitate communication and collaborative efforts get provide a holistic view of the organizational goals to individual employees. To accomplish a single organizational goal, the business environment often relies on many dependencies among tasks performed by individual employees. These dependencies may not always be readily apparent to the individual employee working on a single aspect of a goal. as a result, individual employees often lack an understanding of how their work effort impacts and enables others to contribute to such goals.

Therefore, it would be desirable to have a method and apparatus that take into account at least some of the issues discussed above, as well as other possible issues. For example, it would be desirable to have a method and apparatus that overcome issues with information organization methods and systems that result in a lack of understanding of the collaborative efforts needed to accomplish business goals of the organization.

SUMMARY

In one illustrative embodiment, a graphical display system comprises a computer system and an activity-based relationship system in communication with the display system. The activity-based relationship system receives identity information for at least one entity for determining activity-based relationships. The activity-based relationship system captures On-line activity data of the at least one entity. The online activity can include a plurality of on-line activities consisting of sending and receiving email, sending and receiving meeting invitations, storing and retrieving data files, accessing URLs, VoIP calls, on-line meeting activity, travel activity and on-line postings. The activity-based relationship system analyzes the activity data to identify other entities and subjects of interest. The activity-based relationship system determines relationship activity metrics. The relationship activity metrics can comprise frequency, quantity, and duration metrics for at least a portion of the identified other entities and subjects of interest. The activity-based relationship system identifies network connection diagram resolution threshold data element that is applicable to each component of the determined relationship activity metrics. The activity-based relationship system then presents, on a graphical display system, an interactive activity-based connection diagram. The activity-based connection diagram includes nodes representing entities and subjects of interest with relationship activity metrics that exceed the resolution threshold value. The activity-based connection diagram includes connections among the nodes that represent at least one of the frequency, quantity, and duration metrics for activity data that includes the connected nodes.

In another illustrative embodiment, a method of representing relationships among a plurality of entities based on analysis of on-line activity of the entities is provided. A computer system receives identity information for at least one entity for determining activity-based relationships. The computer system captures On-line activity data of the at least one entity. The online activity can include a plurality of on-line activities consisting of sending and receiving email, sending and receiving meeting invitations, storing and retrieving data files, accessing URLs, VoIP calls, on-line meeting activity, travel activity and on-line postings. The computer system analyzes the activity data to identify other entities and subjects of interest. The computer system determines relationship activity metrics. The relationship activity metrics can comprise frequency, quantity, and duration metrics for at least a portion of the identified other entities and subjects of interest. The computer system identifies network connection diagram resolution threshold data element that is applicable to each component of the determined relationship activity metrics. The computer system then presents, on a graphical display system, an interactive activity-based connection diagram. The activity-based connection diagram includes nodes representing entities and subjects of interest with relationship activity metrics that exceed the resolution threshold value. The activity-based connection diagram includes connections among the nodes that represent at least one of the frequency, quantity, and duration metrics for activity data that includes the connected nodes.

In another illustrative embodiment, a computer program product for representing relationships among a plurality of entities based on analysis of on-line activity of the entities is provided. The computer program product comprises a computer readable storage media. First program code, stored on the computer readable storage media, receives identity information for at least one entity for determining activity-based relationships. First program code, stored on the computer readable storage media, captures On-line activity data of the at least one entity. The online activity can include a plurality of on-line activities consisting of sending and receiving email, sending and receiving meeting invitations, storing and retrieving data files, accessing URLs, VoIP calls, on-line meeting activity, travel activity and on-line postings. Second program code, stored on the computer readable storage media, analyzes the activity data to identify other entities and subjects of interest. Third program code, stored on the computer readable storage media, determines relationship activity metrics. The relationship activity metrics can comprise frequency, quantity, and duration metrics for at least a portion of the identified other entities and subjects of interest. Fourth program code, stored on the computer readable storage media, identifies network connection diagram resolution threshold data element that is applicable to each component of the determined relationship activity metrics. Fifth program code, stored on the computer readable storage media, then presents, on a graphical display system, an interactive activity-based connection diagram. The activity-based connection diagram includes nodes representing entities and subjects of interest with relationship activity metrics that exceed the resolution threshold value. The activity-based connection diagram includes connections among the nodes that represent at least one of the frequency, quantity, and duration metrics for activity data that includes the connected nodes.

BRIEF DESCRIPTION OF THE DRAWINGS

The novel features believed characteristic of the illustrative embodiments are set forth in the appended claims. The illustrative embodiments, however, as well as a preferred node of use, further objectives and features thereof, will best be understood by reference to the following detailed description of an illustrative embodiment of the present disclosure when read in conjunction with the accompanying drawings, wherein:

FIG. 1 is an illustration of a block diagram of an activity-based relationship environment, depicted in accordance with an illustrative embodiment;

FIG. 2 is an illustration of a modular depiction of a relationship auditor for identifying activity-based relationships, depicted in accordance with an illustrative embodiment;

FIG. 3 is an illustration of a graphic user interface depicting an activity-based connection diagram, depicted according to an illustrative embodiment;

FIG. 4 is an illustration of a graphic user interface depicting any user interaction with a group of related nodes with an activity-based connection diagram, depicted according to an illustrative embodiment;

FIG. 5 is an illustration of a graphic user interface depicting a user interaction with a single node within an activity-based connection diagram, depicted according to an illustrative embodiment;

FIG. 6 is an illustration of a graphic user interface depicting a user interaction showing a search for similar nodes, depicted according to an illustrative embodiment;

FIG. 7 is an illustration of a graphic user interface depicting a user interaction showing a search for a particular node, depicted according to an illustrative embodiment;

FIG. 8 is an illustration of a graphic user interface depicting connected nodes for a single node within an activity-based connection diagram, depicted according to an illustrative embodiment;

FIG. 9 is an illustration of a graphic user interface depicting a user interaction with an entity, depicted according to an illustrative embodiment;

FIG. 10 is an illustration of a flowchart of a process for presenting an activity-based connection diagram, depicted according to an illustrative embodiment; and

FIG. 11 is an illustration of a block diagram of a data processing system, depicted in accordance with an illustrative embodiment.

DETAILED DESCRIPTION

The illustrative embodiments recognize and take into account one or more different considerations. For example, the illustrative embodiments recognize and take into account that techniques for network maps currently exist. However, they are, once generated, often static to the viewer. Furthermore, current network maps may be limited to viewing only a particular type of connection between nodes of the network, such as connections between individuals. The illustrative embodiments recognize and take into account that a particular view of the data presented in a network map may not correspond to a user's understanding of the same network or relationships within it.

The illustrative embodiments recognize and take into account that determining relationships among diverse data types from a range of different data sources itself presents challenges, and may be more difficult than desired. The illustrative embodiments also recognize and take into account that understanding the connectedness between individuals in a group and between groups within an organization based on current network maps may be more difficult than desired.

A need exists for methods and systems for allowing the understanding of the activity-based interconnections within an organization. Understanding the connectedness between individuals in a group and between groups may facilitate organizational understanding and planning. For example, a need exists for understanding organizational power of different individuals, who is the connector within an organization or team, and whether groups work together as closely as desired, for example sales and legal organizations, whether a team appears to be missing a critical skill, such as reflected by having a high degree of connection to an individual or organization outside the team. Further, a need exists for methods and systems for gathering multiple types of information across a variety of data sources and integrating the data for display in a manner that allows a user to rapidly move between data types displayed.

Thus, the illustrative embodiments provide a method and apparatus for graphically displaying data within activity-based connection system that provide improved visibility and navigation of relationships and connections among individuals, organizations, tasks, and locations. The activity-based connection system includes techniques that facilitate dynamic user-direction for the collection, analysis and interactive presentation of relationship and connection information. Relationship assessment techniques of the activity-based connection system may be applied to a wide variety of data types that may be gathered from a plurality of data sources existing across disparate devices, networks and in the cloud.

Activity-based relationship information and organizational method and systems described herein may facilitate exploring and discovering the value of connections between and among individuals, organizations, tasks, data sets, computer networks, and transportation networks. The inventive concepts of the activity-based relationship system expand relationship and connection analysis substantively by allowing a user to interactively gather and analyze disparate types of information, thereby providing a user with a richer, nuanced view of how different types of entities, represented by many kinds of information, are potentially connected to each other.

With reference now to the Figures and in particular with reference to FIG. 1, an illustration of a block diagram of an activity-based relationship environment 100 is depicted in accordance with an illustrative embodiment. Activity-based relationship environment 100 includes activity-based relationship system 102.

Activity-based relationship system 102 is used to perform operations with respect to employer personnel 104. The operations can be, for example but not limited to, at least one of providing communication between, and distributing ideas amongst employer personnel 104, so that they can gain a greater understanding of how their individual work effort impacts and enables others of employer personnel 104 to contribute to the activities, goals, deliverables, and the like of employer 106. As depicted, employer personnel 104 are people who are employed by or associated with an entity for which activity-based relationship system 102 is implemented, such as employer 106. For example, employer personnel 104 include at least one of employees, administrators, managers, supervisors, and third parties associated with employer 106. As depicted, employer personnel 104 includes employee 108.

As used herein, the phrase “at least one of,” when used with a list of items, means different combinations of one or more of the listed items may be used and only one of each item in the list may be needed. In other words, at least one of means any combination of items and number of items may be used from the list but not all of the items in the list is required. The item may be a particular object, thing, or a category.

For example, without limitation, “at least one of item A, item B, or item C” may include item A, item A and item B, or item B. This example also may include item A, item B, and item C or item B and item C. Of course, any combinations of these items may be present. In some illustrative examples, “at least one of” may be, for example, without limitation, two of item A; one of item B; and ten of item C; four of item B and seven of item C; or other suitable combinations.

Employer personnel 104 may include administrators. Administrators are designated ones of employer personnel 104 that are responsible for managing at least one of the tools, hardware, and software that facilitate generating, controlling, and presenting content within activity-based relationship system 102.

Employer personnel 104 may include managers and supervisors. Managers and supervisors are designated ones of employer personnel 104 that are responsible for overseeing content entered into activity-based relationship system 102 by employees 108, determining access by employees 108 to content within activity-based relationship system 102, and generally ensuring that content within activity-based relationship system 102 are appropriate.

As depicted, employer personnel 104 can include third parties. Third parties are other parties with whom employer 108 has a business relationship, but who may not be under the direct supervision of employer 106. In an illustrative embodiment, third parties can include but are not limited to, at least one of customers of employer 106, vendors of employer 106, regulators of employer 106, and other parties which employer 106 has granted access to activity-based relationship system 102.

As depicted, employer personnel 104 includes employee 108. Employee 108 is one of employer personnel 104 that performs user interactions 126 within activity-based relationship system 102. In an illustrative embodiment, employee 108 may also be an administrators, manager, supervisor, or third party. In an illustrative embodiment, employee 108 may perform user interactions 126 within activity-based relationship system 102, such as but not limited to, at least one of posting ideas, posting comments, uploading files, and creating groups within activity-based relationship system 102.

Activity-based relationship system 102 can be implemented in computer system 112, where the computer system is a hardware system includes one or more data processing systems. When more than one data processing system is present, those data processing systems may be in communication with each other using a communications medium. The communications medium may be a network. The data processing systems may be selected from at least one of a computer, a workstation, a server computer, a tablet computer, a laptop computer, a mobile phone, a personal digital assistant (PDA), or some other suitable data processing system.

Activity-based relationship system 102 includes set of entities 114. Set of entities 114 includes at least one entity. As depicted, set of entities 114 includes entity 116.

Set of entities 114 are items that can be organized, viewed, and made available by activity-based relationship system 102 to employer personnel 104 within Activity-based relationship system 102. Each of employer personnel 104 is represented as and correlates to one of set of entities 114 within activity-based relationship system 102. In an illustrative embodiment, activity-based relationship system 102 correlates employee 108 to entity 116.

In an illustrative embodiment, set of entities 114 can correlate to other items besides employer personnel 104. For example, set of entities 114 can correlate to, for example but not limited to, at least one of individuals, groups, organizations, companies, and products, such as equipment, books, and supplies.

As depicted, entity 116 includes identity information 118. Identity information 118 is identifying information used by activity-based relationship system 102 to uniquely identify entity 116 within activity-based relationship system 102. For example, identity information 118 can be at least one of, . . . .

As depicted, entity 116 includes online activities 120. Online activities 120 are user interactions 126 performed by employee 108 that are monitored by activity-based relationship system 102. Online activities 120 can include, for example but not limited to, at least one of sending and receiving email, sending and receiving meeting invitations, storing and retrieving data files, accessing URLs, VoIP calls, on-line meeting activity, travel activity and on-line postings. Additionally, online activities 120 can include, for example but not limited to, at least one of email, phone calls, calendar, human resources records, social media data, purchase history, search history, legal history, and regulatory history.

Online activities 120 include activity data 122. Activity data 122 is data about online activities 120 that is used by relationship auditor 124 to establish relationships between entity 116 and other entities of set of entities 114. Activity data 122 can include information related to, for example but not limited to, at least one of at least one of sending and receiving email, sending and receiving meeting invitations, storing and retrieving data files, accessing URLs, VoIP calls, on-line meeting activity, travel activity and on-line postings.

Activity-based relationship system 102 monitors online activities 120 of entity 116 with respect to other entities within a set of entities 114 based on the relationships of entity 116 to other entities within a set of entities 114.

Activity-based relationship system 102 includes relationship auditor 124. Relationship auditor 124 determines relationships between entity 116 and others of set of entities 114 based on an application of rule set 128 to relationship activity metrics 130.

Relationship auditor 124 may be implemented in software, hardware, firmware or a combination thereof. When software is used, the operations performed by relationship auditor 124 may be implemented in program code configured to run on hardware, such as a processor unit. When firmware is used, the operations performed by relationship auditor 124 may be implemented in program code and data and stored in persistent memory to run on a processor unit. When hardware is employed, the hardware may include circuits that operate to perform the operations in relationship auditor 124.

In the illustrative examples, the hardware may take the form of a circuit system, an integrated circuit, an application specific integrated circuit (ASIC), a programmable logic device, or some other suitable type of hardware configured to perform a number of operations. With a programmable logic device, the device may be configured to perform the number of operations. The device may be reconfigured at a later time or may be permanently configured to perform the number of operations. Programmable logic devices include, for example, a programmable logic array, programmable array logic, a field programmable logic array, a field programmable gate array, and other suitable hardware devices. Additionally, the processes may be implemented in organic components integrated with inorganic components and may be comprised entirely of organic components excluding a human being. For example, the processes may be implemented as circuits in organic semiconductors.

Relationship activity metrics 130 are relationship between the set of entities 114 as determined by relationship auditor 124 based on the application of rule set 128 to online activities 120. For example, relationship auditor 124 identifies relationships between entity 116 and others of set of entities 114 based on receiving user interactions 126 from employee 108 that relate to the others of set of entities 114. User interactions 126 can be, for example but not limited to at least one of emails and email records, phone records, phone calls, conferences, posts, messages, chats, tweets, appointments, meetings, calendars, organizational charts, job positions, project teams, meetings, memos, social network sites, published literature, HR databases, maps, price sheets, product data sheets.

In an illustrative embodiment, relationship auditor 124 determines relationships between entity 116 and others of set of entities 114 based on a correlation of online activities 120. For example, relationship auditor 124 may determine relationship between entity 116 and others of set of entities 114 based on, for example but not limited to, at least one of a Number of emails exchanged between the entities, a Number of phone calls exchanged between the entities, common Social media connections between the entities, common meetings attended by the entities, common location or physical proximity of the entities, common calendar events invitations conferences and appointments of the entities, common projects of the entities, common groups and organizations of the entities, prior purchase behavior of the entities, prior searching behavior of the entities, common metadata of the entities, a hierarchical organization position with an employer 106 of the entities, common travel activity of the entities, common URL accesses by the entities, and common online network-based meetings of the entities.

Rule set 128 is a set of rules that relationship auditor 124 applies to online activities 120, including activity data 122, in order to determine relationship activity metrics 130. Rule set 128 can include rules related user interactions 126, as well as other rules related to accessed content of user interactions 126.

For example, rule set 128 may include rule by which relationship auditor 124 determines relationship activity metrics 130 for entity 116 based on a number of connections that entity 116 has two others outside of entities 114. In such an embodiment, relationship auditor 124 may give disproportionate weightings to connections for an entity 116 that is connected to a large number of set of entities 114, or a small number of set of entities 114. For example, if entity 116 is connected to only a small number of other entities in set of entities 114, relationship auditor 124 may assume that the small number of connections are more intimately connected, and therefore give those connections a greater weight. Conversely, if entity 116 is connected to a large number of other entities in sets of entities 114, relationship auditor 124 may assume that those connections are more ephemeral, and therefore give those connections a lesser weight. For example, Weights may account for or discard unusual events, such as a high number of connections during a single period, which may reflect a temporary connection that is relevant only to an event, as opposed to a persistent connection.

Rule set 128 may include a rule by which relationship auditor 124 determines relationship activity metrics 130 for entity 116 based on a frequency of interactions between entity 116 and another of set of entities 114. In this embodiment, relationship auditor 124 may assume that entity 116 is more connected to others of set of entities 114 with which entity 116 more frequently communicates. Relationship auditor 124 may therefore give greater weight to connections between entity 116 and those of entities 114 based on the more frequent communication. For example, Weights may be based on the regularity of connection, such as to distinguish short-term versus persistent connections.

Rule set 128 may include rule by which relationship auditor 124 determines relationship activity metrics 130 for entity 116 based on a links of interaction between entity 116 and another of set of entities 114. In this embodiment, relationship auditor 124 may assume that a more lengthy transaction between entity 116 and the other of set of entities 114 is indicative of a greater degree of connectivity. Relationship auditor 124 may therefore give a greater weight to connections between entity 116 and the other set of entities 114 based on the duration of the interaction. For example, Weights may be based on the duration of connection, such as to distinguish short-term versus persistent connections.

Rule set 128 may include rule by which relationship auditor 124 determines relationship activity metrics 130 for entity 116 based on a tone of the interaction between entity 116 and the other of set of entities 114. In this embodiment, relationship auditor 124 may assume that interactions of a more personal nature may indicate a greater degree of connectivity. Relationship auditor 124 may therefore give greater weight connections between entity 116 and another of set of entities 114 based on the personal nature of the interaction. Conversely, relationship auditor 124 may assume that interactions of a strictly business nature may indicate a lesser degree of connectivity. Relationship auditor 124 may their give a lesser way to connections between entity 116 and another of set of entities 114 based on the business nature of the interaction.

According to an illustrative embodiment, rule set 128 may include a rule by which relationship auditor 124 determines relationship activity metrics 130 for entity 116 based on a frequency of the interactions between entity 116 and another of set of entities 114. In this embodiment, relationship auditor 124 may assume that more frequent interactions between entity 116 and the other of set of entities 114 is indicative of a greater degree of connectivity. Relationship auditor 124 may therefore give greater weight to the connection. Conversely, relationship auditor 124 may assume that less frequent or single interactions between entity 116 and the other set of entities 114 is indicative of a lesser degree of connectivity. Relationship auditor 124 may therefore give a lesser weight to the connection. For example, emails separated on average by minutes might indicate a very high connection, while emails separated by days might indicate a low connection.

According to an illustrative embodiment, rule set 128 may include rule by which relationship auditor 124 determines relationship activity metrics for entity 116 based on density information regarding the interaction itself, such as a density of a set of entities 114 participating. For example, the rule may include the based on a number of people involved in the interaction. A face-to-face lunch encounter between entity 116 and other upset of entities 114 may therefore indicate a greater degree of connectivity and relationship auditor 124 can give preferential waiting to such interaction. Conversely, an encounter at a business meeting between entity 116 and a large number of set and 114 may not provide the same degree of connectivity. Therefore, relationship auditor 124 may give a lesser weight to the business meeting, based on the volume of set of entities 114 that may be in attendance.

According to an illustrative embodiment, rule set 128 may include rule by which relationship auditor 124 determines relationship activity metrics 130 for entity 116 based on a geographic proximity of employee 108 to another of set of employer personnel 104. In such an embodiment, relationship auditor 124 may assume that a closer geographic proximity may be indicative of a greater degree of connectivity. Relationship auditor 124 may therefore give a greater weight to connections that are within some geographic proximity.

According to an illustrative embodiment, rule set 128 may include rule by which relationship auditor 124 determines relationship activity metrics 130 by leveraging social media information for entity 116. In such an embodiment, relationship auditor 124 may give greater weight to relationships between entity 116 and set of entities 114 that are a first-degree connection, as determined from the social media information. Relationship auditor 124 may give a lesser way to connections between entity 116 and others of set of entities 114 that our second degree connection, or third-degree connections, etc.

According to an illustrative embodiment, rule set 128 may include rule by which relationship auditor 124 determines relationship activity metrics 130 by identifying accessed content regarding of activity data 122 from online activities 120 of entity 116. In such an embodiment, relationship auditor 124 may use pricing sheets, product information, and technical specifications related to activity data 122 for online activities 120 of entity 116. Relationship auditor 124 may therefore assume a relationship between entity 116 and other of set of entities 114 based on the commonality of accessed content.

According to an illustrative embodiment, relationship auditor 124 may leverage an expected interaction between entity 116 and set of entities 114 can provide employer 106 with a greater understanding of the degree to which entity 116 is connected to others of set of entities 114. The relationship activity metrics 130 may facilitate understanding of the organizational power of employee 108, who is the connector within employer personnel 104, whether employer personnel 104 work together as closely as desired, for example sales and legal organizations, whether team of employer personnel 104 appears to be missing a critical skill, such as reflected by having a high degree of connection to employee 108 or employer personnel 104 outside the team, and the like. Similarly, employer 106 can use relationship activity metrics 130 to identify failure of employee 108 to connect as needed to successfully complete a project or as required for compliance with various regulations. The degree to which employee 108 is connected to others of employer personnel 104 may therefore be used as one factor in the evaluation and career planning of employee 108.

As depicted, relationship activity metrics 130 includes activity types 132. Activity types 132 are online activities 120, and the associated activity data 122, from which relationship auditor 124 determines relationships between set of entities 114 based on the application of rule set 128. For example, activity types 132 may include activities between entity 116 and another set of entities 114, including but not limited to, at least one of phone calls, messages, chats, tweets, posts, shared contacts, commonly attended conferences, commonly attended meetings, common projects, common committees, common organization memberships, common skill sets, common product features, common product specifications, common product costs, geographical distances, as well as timing, products, markets, filings, and legal actions.

In an illustrative embodiment, relationship auditor 124 can identify these activities by data mining one or more of emails and email records, phone records, phone calls, conferences, posts, messages, chats, tweets, appointments, meetings, calendars, organizational charts, job positions, project teams, meetings, memos, social network sites, published literature, HR databases, maps, price sheets, product data sheets, from a plurality of data sources. As depicted, relationship auditor 124 can identify these activities from entity data source 134. In an illustrative embodiment, Entity data source 134 can be one or more data sources existing across disparate devices, networks and in the cloud.

In an illustrative embodiment, relationship auditor 124 may use a plurality of factors with different weightings for each of activity types 132 to determine the weights for the nodes and the degree of connectedness. For example, in an illustrative and non-limiting example, individual emails may be given a weight of one and common meetings a weight of three when calculating the degree of connectedness between individuals.

As depicted, relationship activity metrics 130 includes connection strength 136. Connection strength 136 is a measure of the relative connection strength between entity 116 and others of set of entities 114 based on the accumulated online activities 120 there between. In an illustrative embodiment, Connection strength 136 may be a numerical score, based on weights of the accumulated online activities 120 between entity 116 and the other of set of entities 114 as determined by relationship auditor 124 in relation to rule set 128.

In an illustrative embodiment, connection strength 136 can be determined from it plurality of different metrics derived from interactions between the entities. For example, connection strength 136 can be determined from, but not limited to, at least one of a number of interactions between the entities, any amount of time or duration of the interactions between the entities, a content length of particular interaction between the entities, such as an e-mail, a frequency of interaction between the entities, the consistency of interactions between the entities, a tenor of interactions between the entities, such as for example whether the interaction is cordial, hostile, personal, or businesslike, a content of the interaction between the entities based on keywords, topics, tags, and subject lines, and a specificity of the interaction between the entities, such as for example point-to-point as opposed to broadcast e-mails.

As depicted, activity-based relationship system 102 includes display system 138. In this illustrative example, display system 138 can be a group of display devices. A display device in display system 138 may be selected from one of a liquid crystal display (LCD), a light emitting diode (LED) display, an organic light emitting diode (OLED) display, and other suitable types of display devices.

In this illustrative example, display system 138 includes graphic user interface 140. In this illustrative example, activity-based relationship system 102 can display information such as for example, at least one of activity-based connection diagram 142, or other suitable information in graphic user interface 140.

Activity-based connection diagram 142 is an interactive connection map for set of entities 114 that guides employee 108 in exploring and discovering the value of connections between and among employer personnel 104, as well as other, organizations, tasks, data sets, computer networks, transportation networks as they relate to employer 106. Together with relationship auditor 124, activity-based connection diagram 142 allows employee 108 to interactively gather and analyze disparate types of information, such as online activities 120. Activity-based connection diagram 142 therefore provides employee 108 with a richer, nuanced view of how different ones of set of entities 114, represented by many kinds of activity data 122, are potentially connected to each other.

As depicted, activity-based connection diagram 142 includes set of nodes 144. Set of nodes 144 is a graphical rendition of the set of entities 144 as displayed within activity-based connection diagram 142 on the graphic user interface 140. Each of set of nodes 144 corresponds to one of set of entities 114. As depicted, set of nodes 144 includes node 146. Node 146 corresponds to entity 116. Node 146 is a graphical rendition of the entity 116 as displayed within activity-based connection diagram 142 on the graphic user interface 140.

Each set of nodes 144 can be represented as having a different size has displayed within activity-based connection diagram 142. For example, size of node 146 may represent relative weight or value of node 146, as compared to other subset of nodes 144.

As depicted, activity-based connection diagram 142 includes connections 148. Connections 148 is a graphical rendition of relationship activity metrics 130 as displayed within the activity-based connection diagram 142 on graphic user interface 140. Each of connections 148 therefore reference is representative of a connection between ones of set of entities 114.

In an illustrative embodiment, connections 148 may be depicted within activity-based connection diagram 142 as a line connecting node 146 to others of set of nodes 144. Activity-based connection diagram 142 may vary the length or weight of the line connecting node 146 and the other of set of nodes 144 two indicate degree of connectedness between entity 116 and the other of set of entities 114.

In an illustrative embodiment, activity-based connection diagram 142 is not static. Instead, activity-based relationship system 102 can receive additional user interactions 126 to create additional online activities 120 in real time, or near real-time. Relationship auditor 124 can update relationship activity metrics 130 based on the changes to online activities 120 and activity data 122, such that the updated online activities 120 are displayed in activity-based connection diagram 142.

As depicted, activity-based connection diagram 142 includes resolution filters 150. The resolution filters 150 is a filter that allows employee 108 to graphically filter activity-based connection diagram 142 based on a particular one of relationship activity metrics 130, such as activity type 132 and connection strength 136.

Specified type 152 is one of resolution filters 150 that allows employee 108 two filter activity-based connection diagram 142 based on selected one of activity types 132. In an illustrative embodiment, activity-based connection diagram 142 can selectively display only those of connections 148 between set of nodes 144 based on the selection of specified type 152 by employee 108. Activity-based connection diagram 142 may therefore selectively display only of those connections 148 between set of nodes 144 that corresponds to specified type 152 selection of, at least one of For example, activity types 132 may include activities between entity 116 and another set of entities 114, including but not limited to, at least one of phone calls, messages, chats, tweets, posts, shared contacts, commonly attended conferences, commonly attended meetings, common projects, common committees, common organization memberships, common skill sets, common product features, common product specifications, common product costs, geographical distances, as well as timing, products, markets, filings, and legal actions. Connections 148 between set of nodes 144 that are not based on the selected specified type 152 are therefore not displayed within the filtered view of activity-based connection diagram 142.

As depicted, resolution filters 150 include strength threshold 154. Strength threshold 154 is one of resolution filters 150 that allows employee 108 to selectively display only those of connections 148 between set of nodes 144 based on specified connection strength 136. By specifying strength threshold 154, employee 108 can identify connections between ones of set of entities 114 that have achieved a desired connection strength 136, based on the application of rule set 128 to online activities 120

As a result, computer system 112 operates as a special purpose computer system in which relationship auditor 124 in computer system 112 provides improved visibility and navigation of relationships and connections among set of entities 114, including individuals, organizations, tasks, locations and the like. Relationship auditor 124 includes techniques that facilitate dynamic user-direction for the collection, analysis and interactive presentation of relationship and connection information between set of entities 114. Connection and relationship analysis by relationship auditor 124 and presentation in activity-based connection diagram 142 guides employee 108 in exploring and discovering the value of connections between and among individuals, organizations, tasks, data sets, computer networks, and transportation networks

Relationship auditor 124 fundamentally expands relationship and connection analysis substantively by allowing employee 108 to interactively gather and analyze disparate types of activity data 122. Relationship auditor 124 therefore provides employee 108 with a richer, nuanced view of how different ones of set of entities 114, represented by many kinds of online activities 120 and related activity data 122, are potentially connected to each other. Thus, relationship auditor 124 transforms computer system 112 into a special purpose computer system as compared to currently available general computer systems that do not have relationship auditor 124.

The illustration of activity-based relationship system 102 in FIG. 1 is not meant to imply physical or architectural limitations to the manner in which an illustrative embodiment may be implemented. Other components in addition to or in place of the ones illustrated may be used. Some components may be unnecessary. Also, the blocks are presented to illustrate some functional components. One or more of these blocks may be combined, divided, or combined and divided into different blocks when implemented in an illustrative embodiment.

For example, relationship auditor 124 may be used to track a wide variety of data types that may be gathered from a plurality of data sources existing across disparate devices, networks and in the cloud. Activity-based relationship system 102 may therefore include a plurality of data sets 156, stored in entity set data source 158. Each of data sets 156 contains identity information in online activities for a different set of entities, such as set of entities 114.

As another example, activity-based relationship system 102 is a Business-centric system for generating activity-based connection diagram 142 based on one of data sets 156 for business-related set of entities 114. Connections 148 can be manipulated by way of user interactions 126 in a graphic user interface 140, such that activity-based connection diagram 142 performs business related functions. The business-related functions can be, for example but not limited to, at least one of organizational analysis, measuring worker effectiveness, task tracking, traffic analysis, activity-based organization charting, path optimization, and activity-based scenario modeling. Additionally, manipulation of activity-based connection diagram 142 through user interactions 126 may result in at least one of updates to activity data 122 to facilitate real world interactions between employer personnel 104. These interactions can be, for example but not limited to such as introductions between employer personnel 104, and the initiation of real world projects in response to analysis of activity data 122 by relationship auditor 124.

As another example, activity-based connection diagram 142 allows for the display and manipulation of connections 148 between set of nodes 144. User interactions 126 with activity-based connection diagram 142 enables employee 108 to easily make changes to activity data 122 by interacting with set of nodes 144 and connections 148 in a graphic user interface 140.

As another example, activity-based connection diagram 142 enables employee 108 to interact with activity-based connection diagram 142 and effect real world changes on the flow of organizational communication with an employer 106. By creating connections 148 between ones of set of nodes 144, activity-based relationship system 102 facilitates introductions among employer personnel 104 and changing distribution of certain information and the like. Thus, activity-based relationship system 102 allows employee 108 to see a level of information flow between organizational entities that is unavailable in traditional network maps that merely provide information regarding the formal structure of the organization.

As another example, activity-based relationship system 102 enables employees 108 to view the connections between an organizational entity and certain types of non-organizational entities such as SEC filings, and lawsuits. Activity-based relationship system 102 allows this type of information to be displayed using a variety of information display techniques while also enabling employee 108 to interact with activity-based connection diagram 142 and effect real world changes.

As another example, activity-based relationship system 102 may facilitate the evaluation of measuring the effectiveness of employer personnel 104, such as employee 108. For some workers, a worker's effectiveness may be evaluated, in part, by understanding to whom they are communicating and to what extent. In some job positions it may be critical that a worker communicates with individuals within his or her organizational group, with other groups or functions within his or her organization and with external companies and organizations. In non-limiting examples, it may be critical that an individual in sales communicate with an individual in the legal department as part of executing non-standard sales agreements. It may be critical that someone in an HR organization is regularly communicating with those individuals and organizations that the person supports. By understanding communication patterns of employee 108, employer 106 may be better able to understand how employee 108 is doing the job, whether certain lines of communication are stronger than others and where there are gaps in communications. Therefore, employer 106 may use relationship activity metrics 130 as determined by relationship auditor 124 to help coach employee 108 regarding the importance of communications, as well as to provide introductions to others of employer personnel 104 two facilitate communication.

As another example, activity-based relationship system 102 may facilitate task tracking of employer personnel 104, such as employee 108. Complex projects may be broken down into a number of subtasks where each of the subtasks comprise, require, or relate to, among other elements, communications between employer personnel 104, as well as communication between employee 108 and different organizational entities such as but not limited to service organizations and functional organizations. Activity-based relationship system 102 may store Estimates regarding the frequency and types of interactions required to complete a given subtask. These estimates may be based on task type, an individual to whom the task is assigned and the like. These estimates may be compared to the actual online activities 120 of the associated set of entities 114 that have occurred as a means of tracking progress toward completion of individual subtasks and completion of the overall project.

As another example, activity-based relationship system 102 may illustrate shipping traffic available as a function of different types of shipping. Connection diagrams are frequently used to show network connectivity, in particular network traffic. However, activity-based relationship system 102 comprises the ability to meld multiple traffic types into activity-based connection diagram 142. Employee 108 can then manipulate activity-based connection diagram 142 through user interactions 126 to see different combinations of traffic. In an illustrative example, employee 108 may wish to see the different types of shipping nodes available between two locations. In the past network diagrams may have shown air shipping, sea shipping on separate diagrams. Activity-based relationship system 102 may illustrate shipping traffic available between different ones of set of nodes 144 as a function of different types of shipping such as air, train, truck and ship, as well as different shipping services such as private, and commercial.

As another example, activity-based relationship system 102 may facilitate Activity-based Organization Charting of employer personnel 104 of employer 106. Employer personnel 104 are typically thought of within employer 106 from a hierarchical perspective. Employees in department A report to manager A who reports to director B who reports to vice president C, and the like. Activity-based relationship system 102 allows for the development of a new view of employer 106 based on the online activities 120 of employer personnel 104. The result may be depicted as activity-based connection diagram 142. Activity-based relationship system 102 can therefore deliver a revolutionary view of an employer 106 that focuses on work-product structuring rather than pure reporting hierarchy structuring.

As another example, activity-based relationship system 102 may facilitate optimal path determination among employer personnel 104. Determining a path from a first point to a second point, such as through employer personnel or even through a physical roadway system may be performed today by using existing mapping technology. In the example of identifying a path through an organization of workers, following a hierarchical organization chart from your location in the chart up to a point that is common between you and your destination and then down through the destination leg from the common point results in a path through fairly well defined, although narrow bottlenecks (e.g. the busy VP that you and the destination have in common). Likewise, using information about streets in a city, even when embellished with current traffic conditions to determine a path can be optimized based on aspects such as travel time.

Activity-based relationship system 102 improves upon known path determination techniques by associating activity data 122 with a source and a destination that may yield a different path than the previous optimization approaches. Relationship auditor 124 therefore allows Path optimization applications of activity-based relationship system 102 to offer path options that are unavailable in conventional mapping approaches.

With reference now to FIG. 2, an illustration of a modular depiction of a relationship auditor for identifying activity-based relationships is depicted in accordance with an illustrative embodiment. As depicted, relationship auditor 200 is an example of relationship auditor 124 of activity-based relationship system 102 of FIG. 1.

As depicted, relationship auditor 200 includes data specification module 202, data relationship module 204, graphic rendering engine 208 and user interactions module 210. Relationship auditor 200 can access one or more database databases 212, such as entity data source 134 and entity set data source 158 of FIG. 1. Relationship auditor 200 may also include analysis module 214.

A user, such as employee 108 of FIG. 1, may access the data specification module 202 to specify a set of data to be displayed, such as one of data sets 156 of FIG. 1. Additionally, the user may specify Related data to be used to weight the representation of the data being displayed and related data to be used to identify the connections between the data being displayed, such as by selection of a rule set, such as rule set 128 of FIG. 1. Data access by data specification module 202 may reside in a single connected database or across a plurality of databases 212.

Data relationship module 204 may then access the data retrieved by data specification module 202. Based on the retrieved data, data relationship module 204 calculates relationship activity metrics, such as relationship activity metrics 130 of FIG. 1. Data relationship module 204 may use a plurality of factors with different ratings to determine the rates for the nodes and the degree of connectedness. In an illustrative and nonlimiting example, e-mails are given a weight of one, and common meetings are given a weight of three when calculating the degree of connectedness between individuals.

Graphics rendering engine 208 utilizes the calculated relationship activity metrics to render an activity-based connection diagram, such as activity-based connection diagram 142 of FIG. 1.

User interaction module 210 enables the user to interact with the activity-based connection diagram and supporting activity data, such as activity data 122 of FIG. 1. The user may interact with the activity-based connection diagram to view additional information about a group of connections, such as connections 148 of FIG. 1. The user may interact with the activity-based connection diagram to view additional information about an individual node in the network, such as node 146 of FIG. 1. Additionally, user interaction module 210 allows the user to search for similar nodes, such as similar ones of set of nodes 144 of FIG. 1. Relationship auditor 200 can also allow user to gather insight into individual connections, such as individual ones of connections 148 in FIG. 1 between node 146 and other subset of nodes 144.

The relationship auditor 200 may be used to gather insight into the connections among individuals and organizations such as by evaluating the number of e-mails exchanged, phone calls, common meetings attended, and the like.

With reference now to FIG. 3, an illustration of graphic user interface depicting an activity-based connection diagram is shown according to an illustrative embodiment. Graphic user interface 300 is an example of graphic user interface 140 of FIG. 1. Activity-based connection diagram 302 is an example of activity-based connection diagram 142 of FIG. 1.

As depicted, activity-based connection diagram 302 includes a plurality of nodes, including node 304, node 306, node 308, node 310, node 312, and node 314. Each of node 304, node 306, node 308, node 310, node 312, and node 314 is a node, such as node 146 of FIG. 1, forming a set of nodes, such as set of nodes 144 of FIG. 1.

As depicted, nodes within activity-based connection diagram 302 are connected to other nodes with connections, such as connections 148 of FIG. 1. As depicted, node 304 is connected to node 306 by connection 316. Node 304 is connected to node 308 by connection 318. Node 304 is connected to node 310 by connection 320. Node 304 is connected to node 312 by connection 322. Node 304 is connected to node 314 by connection 324.

Each of connection 316, connection 318, connection 320, connection 322 and connection 324 is a graphical representation of relationship activity metrics, such as relationship activity metrics 130 of FIG. 1, displayed within graphic user interface 300. The relationship activity metrics displayed as connection 316, connection 318, connection 320, connection 322 and connection 324 can be determined by a relationship auditor, such as relationship auditor 124. The relationship auditor applies a selected rule set, such as rule set 128, to activity data related to each of node 304, node 306, node 308, node 310, node 312, and node 314 in order to determine connection 316, connection 318, connection 320, connection 322 and connection 324. The activity data can be activity data 122 of FIG. 1.

In an illustrative embodiment, each of node 304, node 306, node 308, node 310, node 312, and node 314 can be depicted within activity-based connection diagram 302 is having a different size. The size of a node may represent relative weight or value of the node.

In an illustrative embodiment, each of connection 316, connection 318, connection 320, connection 322 and connection 324 can be depicted within activity-based connection diagram 302 is having a different line weight. The line weight of connections linking nodes may indicate degree of connectedness, as determined from online activities, such as online activities 120 of FIG. 1, and activity data, such as activity to the 122, as described above.

In an illustrative embodiment, a user can interact with activity-based connection diagram 302 through user interactions, such as user interactions 126 of FIG. 1, with graphic user interface 300. For example, by way of user interactions 126, a user can manipulate the manner in which activity-based connection diagram 302 is rendered within graphic user interface 300, such as but not limited to, at least one of choosing to re-center activity-based connection diagram 302 a node of interest, and enlarge a portion of interest of activity-based connection diagram.

In an illustrative embodiment, a user may remove one or more of node 304, node 306, node 308, node 310, node 312, and node 314 from the activity-based connection diagram 302. In response to the removal of one or more nodes from activity-based connection diagram 302, data relationship module 204 of FIG. 2 recalculates the relative weights of the remaining nodes and connections. Graphic rendering engine 208 then updates rendering of activity-based connection diagram 302 in graphic user interface 300 without displaying the removed nodes.

Referring now to FIG. 4, an illustration of a graphic user interface depicting a user interaction with a group of related nodes within an activity-based connection diagram is depicted according to an illustrative embodiment. As depicted, graphic user interface 400 is graphic user interface 300 of FIG. 3 after a user, such as employee 108 of FIG. 1, has input a user interaction, such as user interaction 126 of FIG. 1, with group of nodes 402 of activity-based connection diagram 302.

As depicted, graphic user interface 400 includes group of nodes 402. Group of nodes 402 is a plurality of node having a large degree of interconnectedness between nodes within the group. As depicted, group of nodes 402 includes node 304, node 306, node 308, node 310, node 404, and node 406.

As depicted, node 304 has connections, such as connections 148 of FIG. 1, to node 306, node 308, and node 310. As depicted, node 306 has connections, such as connections 148 of FIG. 1, to node 304, node 308, and node 310. As depicted, no 308 has connections, such as connections 148 of FIG. 1, to node 304, node 306, node 310, node 404, and node 406. As depicted, node 310 has connections, such as connections 148 of FIG. 1, to node 304, node 306, node 308, node 404, and node 406. As depicted, node 404 has connections, such as connections 148 of FIG. 1, to node 308, node 310, and node 406. As depicted, node 406 has connections, such as connections 148 of FIG. 1, to node 308, node 310, and node 404. Based on the high degree of interconnectivity between node 304, node 306, node 308, node 310, node 404, and node 406, a relationship auditor, such as relationship auditor 124 of FIG. 1 can determine that the can be aggregated into a group, such as group of nodes 402.

As depicted, group of nodes 402 correlates to a particular department within an employer, such as employer 106 of FIG. 1. By correlating highly interconnected nodes into group of nodes 402, activity-based connection diagram 302 enables a user to view information 408 that is common to the highly interconnected nodes within group of nodes 402. As depicted, information 408 can include but is not limited to, online activities 120, activity data 122, relationship activity metrics 130, activity type 132, and connection strength 136 of FIG. 1.

With reference now to FIG. 5, an illustration of a graphic user interface depicting a user interaction with a single node within an activity-based connection diagram is depicted according to an illustrative embodiment. As depicted, graphic user interface 500 is a graphic user interface 300 of FIG. 3 after a user, such as employee 108 of FIG. 1 has input a user interaction, such as user interaction 126 of FIG. 1 with node 404 of activity-based connection diagram 302.

Activity-based connection diagram 302 enables a user to view information 502 that went that is related to node 404. When activity-based connection diagram 302 receives a user interaction, such as user interaction 126 of FIG. 1, with node 404, activity-based connection diagram 302 can display information 502 that is related to node 404. As depicted, information 502 can include but is not limited to, online activities 120, activity data 122, relationship activity metrics 130, activity type 132, and connection strength 136 of FIG. 1.

With reference now to FIG. 6, an illustration of a graphic user interface depicting a user interaction showing a search for similar nodes is depicted according to an illustrative embodiment. As depicted, graphic user interface 600 is a graphic user interface 300 of FIG. 3 after a user, such as employee 108 of FIG. 1, has input a user interaction, such as user interaction 126 of FIG. 1, with search filters 602 of graphic user interface 600.

As depicted, graphic user interface 600 includes search filters 602. As depicted, graphic user interface 600 can receive a user interaction, such as user interaction 126 of FIG. 1, into search filters 602. Graphic user interface 600 can then highlight or otherwise graphically indicate nodes and connections with an activity-based connection diagram 302 that correspond to the search terms entered into search filters 602.

As depicted, node 306, node 310, node 312, node 314, and node 406 are graphically indicated as corresponding to search terms entered into search for 600. According to an illustrative embodiment, node 306, node 310, node 312, node 314, and node 406 are graphically indicated by displaying an enlarged depiction of the node within activity-based connection diagram 302.

With reference now to FIG. 7, an illustration of a graphic user interface depicting a user interaction showing a search for a particular node is depicted according to an illustrative embodiment. As depicted, graphic user interface 700 is a graphic user interface 300 of FIG. 3 after a user, such as employee 108 of FIG. 1, has input a user interaction, such as user interaction 126 of FIG. 1, with search filters 602 of graphic user interface 600.

As depicted, node 310 is graphically indicated as corresponding to search terms entered into search filters 602. According to an illustrative embodiment, node 310 is graphically indicated by displaying an enlarged depiction of the node within activity-based connection diagram 302. Additionally, because node 310 is an exact match to the search terms, node 310 can be further graphically by highlighting. Additionally, graphic user interface 700 can display information 702 related to node 310 in response to the exact match between search terms entered into search filters 602 with node 310.

With reference now to FIG. 8, an illustration of a graphic user interface depicting connected nodes for a single node within an activity-based connection diagram is depicted according to an illustrative embodiment. As depicted, graphic user interface 800 is a graphic user interface 300 of FIG. 3 after a user, such as employee 108 of FIG. 1 has input a user interaction, such as user interaction 126 of FIG. 1, selecting node 310 of activity-based connection diagram 302.

As described with reference to FIG. 4, node 310 has connections, such as connections 148 of FIG. 1, to node 304, node 306, node 308, node 404, and node 406. By selecting node 310 from within graphic user interface 300, a user is able to view entities that are connected to node 310.

As depicted, graphic user interface 800 includes node 802, node 804, node 806, node 808, and node 810. As depicted, node 802 corresponds to node 304 and depicts additional information therefore. Node 804 corresponds to node 306 and depicts additional information therefore. Node 806 corresponds to node 308 and depicts additional information therefore. Node 808 corresponds to node 404 and depicts additional information therefore. Node 810 corresponds to node 406 and depicts additional information therefore.

With reference now to FIG. 9, an illustration of a graphic user interface depicting a user interaction with an entity is depicted according to an illustrative embodiment. As depicted, graphic user interface 900 is a graphic user interface 800 of FIG. 8 after a user, such as employee 108 of FIG. 1 has input a user interaction, such as user interaction 126 of FIG. 1, with node 802 of graphic user interface 800 of FIG. 8.

Activity-based connection diagram 302 enables a user to view information 902 that is related to node 802. When activity-based connection diagram 302 receives receive a user interaction, such as user interaction 126 of FIG. 1, with node 802, activity-based connection diagram 302 can display information 902 that is related to node 802. As depicted, information 902 can include but is not limited to, online activities 120, activity data 122, relationship activity metrics 130, activity type 132, and connection strength 136 of FIG. 1.

With reference now to FIG. 10, an illustration of a flowchart of a process for presenting an activity-based connection diagram is depicted according to an illustrative embodiment. Process 1000 may be implemented in relationship auditor 124 in activity-based relationship system 102 of activity-based relationship environment 100 of FIG. 1.

Process 1000 begins by receiving identity information of an entity for activity-based relationship mapping (step 1010). The entity can be entity 114 of FIG. 1. The identity information can be identity information 118 of FIG. 1. In an illustrative embodiment, process 1000 can receive the identity information by retrieving the information from an entity set data source, such as entity set data source 158 of FIG. 1, in response to a user interaction, such as user interaction 126 of FIG. 1.

Process 1000 captures online activity for the entity (step 1020). The online activity can be online activities 120 of FIG. 1. In an illustrative embodiment, process 1000 may also retrieve online activities for the entities from an entity data source, such as entity data source 134 of FIG. 1.

Process 1000 then determines other entities and subjects of interest from the online activity (step 1030). The other entities and subjects of interest can be others of the set of entities 114 of FIG. 1.

Process 1000 determines relationship activity metrics for the entities (step 1040). The relationship activity metrics can be relationship activity metrics 130 of FIG. 1, and can include metrics such as activity type 132 and connection strength 136.

In response to determining the relationship activity metrics for the entities, process 1000 presents an interactive activity-based connection diagram of the entities and subjects of interest with activity metrics (step 1050), with the process terminating thereafter. The activity-based connection diagram can be activity-based connection diagram 142 of FIG. 1. In an illustrative embodiment, process 1000 presents the activity-based connection diagram subject to various resolution filters, such as resolution filters 150 of FIG. 1.

In this manner, the recommendation, scheduling, and monitoring of activities to be performed by employees as part of a health and wellness program can be made more easily as compared to currently used techniques. Because recommended activities are specifically interesting to the employee, employee participation in the health and wellness program is encouraged. As a result, employees are more likely to take advantage of activities offered by and recommended by a health and wellness program. Furthermore, by recommending, scheduling, monitoring, and analyzing activities to be performed by employees as part of a health and wellness program, a desired level of wellness among employees is enabled. These and other tasks may be performed using the visualization of health factors and activity preferences that are manipulated to interact within a graphic user interface to generate a result. As result, an operator may more efficiently perform a wellness task based on the visualization of the health factors and activity preferences in a graphic user interface.

The flowcharts and block diagrams in the different depicted embodiments illustrate the architecture, functionality, and operation of some possible implementations of apparatuses and methods in an illustrative embodiment. In this regard, each block in the flowcharts or block diagrams may represent at least one of a module, a segment, a function, or a portion of an operation or step. For example, one or more of the blocks may be implemented as program code, in hardware, or a combination of the program code and hardware. When implemented in hardware, the hardware may, for example, take the form of integrated circuits that are manufactured or configured to perform one or more operations in the flowcharts or block diagrams. When implemented as a combination of program code and hardware, the implementation may take the form of firmware.

In some alternative implementations of an illustrative embodiment, the function or functions noted in the blocks may occur out of the order noted in the figures. For example, in some cases, two blocks shown in succession may be performed substantially concurrently, or the blocks may sometimes be performed in the reverse order, depending upon the functionality involved. Also, other blocks may be added in addition to the illustrated blocks in a flowchart or block diagram.

Turning now to FIG. 11, an illustration of a block diagram of a data processing system is depicted in accordance with an illustrative embodiment. Data processing system 1100 may be used to implement one or more data processing systems in activity-based relationship system 102 in FIG. 1. In this illustrative example, data processing system 1100 includes communications framework 1102, which provides communications between processor unit 1104, memory 1106, persistent storage 1108, communications unit 1110, input/output unit 1112, and display 1114. In this example, communication framework may take the form of a bus system.

Processor unit 1104 serves to execute instructions for software that may be loaded into memory 1106. Processor unit 1104 may be a number of processors, a multi-processor core, or some other type of processor, depending on the particular implementation.

Memory 1106 and persistent storage 1108 are examples of storage devices 1116. A storage device is any piece of hardware that is capable of storing information, such as, for example, without limitation, at least one of data, program code in functional form, or other suitable information either on a temporary basis, a permanent basis, or both on a temporary basis and a permanent basis. Storage devices 1116 may also be referred to as computer readable storage devices in these illustrative examples. Memory 1106, in these examples, may be, for example, a random access memory or any other suitable volatile or non-volatile storage device. Persistent storage 1108 may take various forms, depending on the particular implementation.

For example, persistent storage 1108 may contain one or more components or devices. For example, persistent storage 1108 may be a hard drive, a flash memory, a rewritable optical disk, a rewritable magnetic tape, or some combination of the above. The media used by persistent storage 1108 also may be removable. For example, a removable hard drive may be used for persistent storage 1108.

Communications unit 1110, in these illustrative examples, provides for communications with other data processing systems or devices. In these illustrative examples, communications unit 1110 is a network interface card.

Input/output unit 1112 allows for input and output of data with other devices that may be connected to data processing system 1100. For example, input/output unit 1112 may provide a connection for user input through at least of a keyboard, a mouse, or some other suitable input device. Further, input/output unit 1112 may send output to a printer. Display 1114 provides a mechanism to display information to a user.

Instructions for at least one of the operating system, applications, or programs may be located in storage devices 1116, which are in communication with processor unit 1104 through communications framework 1102. The processes of the different embodiments may be performed by processor unit 1104 using computer-implemented instructions, which may be located in a memory, such as memory 1106.

These instructions are referred to as program code, computer usable program code, or computer readable program code that may be read and executed by a processor in processor unit 1104. The program code in the different embodiments may be embodied on different physical or computer readable storage media, such as memory 1106 or persistent storage 1108.

Program code 1118 is located in a functional form on computer readable media 1120 that is selectively removable and may be loaded onto or transferred to data processing system 1100 for execution by processor unit 1104. Program code 1118 and computer readable media 1120 form computer program product 1122 in these illustrative examples. In one example, computer readable media 1120 may be computer readable storage media 1124 or computer readable signal media 1126.

In these illustrative examples, computer readable storage media 1124 is a physical or tangible storage device used to store program code 1118 rather than a medium that propagates or transmits program code 1118.

Alternatively, program code 1118 may be transferred to data processing system 1100 using computer readable signal media 1126. Computer readable signal media 1126 may be, for example, a propagated data signal containing program code 1118. For example, computer readable signal media 1126 may be at least one of an electromagnetic signal, an optical signal, or any other suitable type of signal. These signals may be transmitted over at least one of communications links, such as wireless communications links, optical fiber cable, coaxial cable, a wire, or any other suitable type of communications link.

The different components illustrated for data processing system 1100 are not meant to provide architectural limitations to the manner in which different embodiments may be implemented. The different illustrative embodiments may be implemented in a data processing system including components in addition to or in place of those illustrated for data processing system 1100. Other components shown in FIG. 11 can be varied from the illustrative examples shown. The different embodiments may be implemented using any hardware device or system capable of running program code 1118.

Thus, the illustrative embodiments provide a method and apparatus for managing wellness of employees. In one illustrative example, an employee management wellness system receives a group of health factors for activities and group of preferences for activities of the employees. The wellness system identifies a recommendation for an activity for a portion of the employees based on the group health factors, the group of preferences, and information for locations where recommended activities are to occur. The wellness system then sends the recommendation for the activity to the portion of the employees.

In this manner, the recommendation, scheduling, and monitoring of activities to be performed by employees as part of a health and wellness program can be made more easily as compared to currently used techniques. Because recommended activities are specifically interesting to the employee, employee participation in the health and wellness program is encouraged. As a result, employees are more likely to take advantage of activities offered by and recommended by a health and wellness program. Furthermore, by recommending, scheduling, monitoring, and analyzing activities to be performed by employees as part of a health and wellness program, a desired level of wellness among employees is enabled.

The description of the different illustrative embodiments has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the embodiments in the form disclosed. The different illustrative examples describe components that perform actions or operations. In an illustrative embodiment, a component may be configured to perform the action or operation described. For example, the component may have a configuration or design for a structure that provides the component an ability to perform the action or operation that is described in the illustrative examples as being performed by the component. In particular, wellness manager is configured to perform the different operations described as well as other operations using at least one of program code, hardware, firmware, or other suitable components.

Many modifications and variations will be apparent to those of ordinary skill in the art. Further, different illustrative embodiments may provide different features as compared to other desirable embodiments. The embodiment or embodiments selected are chosen and described in order to best explain the principles of the embodiments, the practical application, and to enable others of ordinary skill in the art to understand the disclosure for various embodiments with various modifications as are suited to the particular use contemplated.

Claims

1. A method of determining connections among a set of entities, the method comprising:

receiving identity information for at least one entity in the set of entities for determining activity-based relationships;

capturing on-line activity data of the at least one entity;

analyzing the activity data of the at least one entity to identify others entities among a set of entities and subjects of interest for the at least one entity;

determining relationship activity metrics for the at least one entity, the relationship activity metrics comprising metrics for interactions between the at least one entity and the others entities among a set of entities, and metrics for interactions between the at least one entity and the subjects of interest; and

presenting, based on the relationship activity metrics, the at least one entity, the other entities, and the subjects of interest as a set of nodes in an activity-based connection diagram with relationship activity metrics, and

presenting, based on the relationship activity metrics, connections among the nodes in the activity-based connection diagram.

2. The method of claim 1, wherein the on-line activity data of the at least one entity comprises on-line activities selected from a list consisting of sending and receiving email, sending and receiving meeting invitations, storing and retrieving data files, accessing URLs, VoIP calls, on-line meeting activity, travel activity, on-line postings, and combinations thereof.

3. The method of claim 1, further comprising:

identifying connections the at least one entity and the others entities among a set of entities by data mining records of the at least one entity, the records selected from a list consisting of one or more of emails and email records, phone records, phone calls, conferences, posts, messages, chats, tweets, appointments, meetings, calendars, organizational charts, job positions, project teams, meetings, memos, social network sites, published literature, HR databases, maps, price sheets, product data sheets, and combinations thereof

4. The method of claim 1, wherein the relationship activity metrics are selected from a list consisting of comprising frequency interactions between the at least one entity and the others entities, quantity interactions between the at least one entity and the others entities, duration of interactions between the at least one entity and the others entities, and combinations thereof.

5. The method of claim 1, further comprising:

applying a set of resolution filters to the relationship activity metrics; and wherein the step of presenting the other entities and the subjects of interest further comprises:

presenting only ones of the other entities and ones of the subjects of interest in the Activity-based connection diagram that have relationship activity metrics with the at least one entity that meets the set of resolution filters; and

presenting only connections between the at least one entity and ones of the other entities, and connections between the at least one entity and ones of the subjects of interest in the Activity-based connection diagram that have relationship activity metrics that meets the set of resolution filters.

6. The method of claim 5, wherein the set of resolution filters is selected from the group consisting of a connection strength threshold and a specified connection type.

7. The method of claim 6, wherein the connection strength threshold is a threshold that represent at least one of frequency of interactions between the at least one entity and the others entities, quantity of interactions between the at least one entity and the others entities, duration of interactions between the at least one entity and the others entities, and combinations thereof.

8. The method of claim 6, wherein specified connection type is selected from the group consisting of one or more of email, phone calls, messages, chats, tweets, posts, contacts, conferences, meetings, projects, committees, organizations, skills, features, specifications, costs, distances, timing, products, markets, filings, legal actions, and combinations thereof.

9. The method of claim 1, further comprising:

capturing on-line activity data for the others entities; and wherein the step of determining relationship activity metrics for the at least one entity further comprises:

determining relationship activity metrics for the at least one entity, the relationship activity metrics further comprising metrics for interactions between the others entities among a set of entities and the at least one entity, and metrics for interactions between the subjects of interest and the at least one entity, wherein on-line activity for the other entities is captured prior to determining relationship activity metrics for the at least one entity.

10. The method of claim 1, further comprising:

updating the relationship activity metrics for the at least one entity in near real-time based on capturing new on-line activity of the entity, the other entities, and combinations thereof.

11. The method of claim 1, further comprising:

receiving a manipulation of an interactive network connection diagram; and

in response to receiving the manipulation, a data relationship module altering the connections between nodes; and

presenting, based on the relationship activity metrics, updated connections among the nodes in the interactive network connection diagram based on the alteration.

12. The method of claim 1, wherein objects of interest may include at least one of people, organizations, enterprises, government entities, regulatory entities, markets, projects, routes, and products.

13. The method of claim 1, wherein the step of determining relationship activity metrics for the at least one entity further comprises:

calculating a strength of the connections based on a rule set.

14. The method of claim 13, wherein the rule set includes one or more rules selected from the group consisting of a rule using a number of connections, a rule using a frequency of interactions, a rule using a length of interactions, a rule using a tone of interactions, a rule using a density of interaction, a rule using a geographic proximity, a rule using pricing sheets, a rule using a feature and technical specification, a rule leveraging social media information, and a rule leveraging expected interaction compared to measured interaction

15. A computer system comprising:

a display system; and

a relationship auditor of an activity-based relationship system in the computer system in communication with the display system, wherein the relationship auditor: receives identity information for at least one entity in a set of entities for determining activity-based relationships; analyzing on-line activity data of the at least one entity to identify others entities among a set of entities and subjects of interest for the at least one entity; determines relationship activity metrics for the at least one entity, the relationship activity metrics comprising metrics for interactions between the at least one entity and the others entities among a set of entities, and metrics for interactions between the at least one entity and the subjects of interest; presents, based on the relationship activity metrics, the at least one entity, the other entities, and the subjects of interest as a set of nodes in an Activity-based connection diagram with relationship activity metrics, and presents, based on the relationship activity metrics, connections among the nodes in the activity-based connection diagram.

16. The computer system of claim 15, wherein the on-line activity data of the at least one entity comprises on-line activities selected from a list consisting of sending and receiving email, sending and receiving meeting invitations, storing and retrieving data files, accessing URLs, VoIP calls, on-line meeting activity, travel activity, on-line postings, and combinations thereof.

17. The computer system of claim 15, wherein the relationship auditor:

identifies connections the at least one entity and the others entities among a set of entities by data mining records of the at least one entity, the records selected from a list consisting of one or more of emails and email records, phone records, phone calls, conferences, posts, messages, chats, tweets, appointments, meetings, calendars, organizational charts, job positions, project teams, meetings, memos, social network sites, published literature, HR databases, maps, price sheets, product data sheets, and combinations thereof.

18. The computer system of claim 15, wherein the relationship activity metrics are selected from a list consisting of comprising frequency interactions between the at least one entity and the others entities, quantity interactions between the at least one entity and the others entities, duration of interactions between the at least one entity and the others entities, and combinations thereof.

19. The computer system of claim 15, wherein the relationship auditor:

applies a set of resolution filters to the relationship activity metrics, wherein the set of resolution filters is selected from the group consisting of a connection strength threshold and a specified connection type, wherein the connection strength threshold is a threshold that represent at least one of frequency of interactions between the at least one entity and the others entities, quantity of interactions between the at least one entity and the others entities, duration of interactions between the at least one entity and the others entities, and combinations thereof, wherein specified connection type is selected from the group consisting of one or more of email, phone calls, messages, chats, tweets, posts, contacts, conferences, meetings, projects, committees, organizations, skills, features, specifications, costs, distances, timing, products, markets, filings, legal actions, and combinations thereof; and wherein the step of presenting the other entities and the subjects of interest further comprises:

presenting only ones of the other entities and ones of the subjects of interest in the Activity-based connection diagram that have relationship activity metrics with the at least one entity that meets the set of resolution filters; and

presenting only connections between the at least one entity and ones of the other entities, and connections between the at least one entity and ones of the subjects of interest in the Activity-based connection diagram that have relationship activity metrics that meets the set of resolution filters.

20. The computer system of claim 15, wherein the step of determining relationship activity metrics for the at least one entity further comprises:

the relationship auditor calculating a strength of the connections based on a rule set, wherein the rule set includes one or more rules selected from the group consisting of a rule using a number of connections, a rule using a frequency of interactions, a rule using a length of interactions, a rule using a tone of interactions, a rule using a density of interaction, a rule using a geographic proximity, a rule using pricing sheets, a rule using a feature and technical specification, a rule leveraging social media information, and a rule leveraging expected interaction compared to measured interaction

21. A computer program product for determining connections among a set of entities, the computer program product comprising:

a computer readable storage media;

first program code, stored on the computer readable storage media, for receiving identity information for at least one entity in the set of entities for determining activity-based relationships;

second program code, stored on the computer readable storage media, for analyzing on-line activity data of the at least one entity to identify others entities among a set of entities and subjects of interest for the at least one entity;

third program code, stored on the computer readable storage media, for determining relationship activity metrics for the at least one entity, the relationship activity metrics comprising metrics for interactions between the at least one entity and the others entities among a set of entities, and metrics for interactions between the at least one entity and the subjects of interest;

fourth program code, stored on the computer readable storage media, for presenting, based on the relationship activity metrics, the at least one entity, the other entities, and the subjects of interest as a set of nodes in an activity-based connection diagram with relationship activity metrics, and

fifth program code, stored on the computer readable storage media, for presenting, based on the relationship activity metrics, connections among the nodes in the activity-based connection diagram.

22. The computer program product of claim 21, wherein the on-line activity data of the at least one entity comprises on-line activities selected from a list consisting of sending and receiving email, sending and receiving meeting invitations, storing and retrieving data files, accessing URLs, VoIP calls, on-line meeting activity, travel activity, on-line postings, and combinations thereof.

23. The computer program product of claim 21, further comprising:

sixth program code, stored on the computer readable storage media, for identifying connections the at least one entity and the others entities among a set of entities by data mining records of the at least one entity, the records selected from a list consisting of one or more of emails and email records, phone records, phone calls, conferences, posts, messages, chats, tweets, appointments, meetings, calendars, organizational charts, job positions, project teams, meetings, memos, social network sites, published literature, HR databases, maps, price sheets, product data sheets, and combinations thereof.

24. The computer program product of claim 21, wherein the relationship activity metrics are selected from a list consisting of comprising frequency interactions between the at least one entity and the others entities, quantity interactions between the at least one entity and the others entities, duration of interactions between the at least one entity and the others entities, and combinations thereof.

25. The computer program product of claim 21, further comprising:

sixth program code, stored on the computer readable storage media, for applying a set of resolution filters to the relationship activity metrics, wherein the set of resolution filters is selected from the group consisting of a connection strength threshold and a specified connection type, wherein the connection strength threshold is a threshold that represent at least one of frequency of interactions between the at least one entity and the others entities, quantity of interactions between the at least one entity and the others entities, duration of interactions between the at least one entity and the others entities, and combinations thereof, wherein specified connection type is selected from the group consisting of one or more of email, phone calls, messages, chats, tweets, posts, contacts, conferences, meetings, projects, committees, organizations, skills, features, specifications, costs, distances, timing, products, markets, filings, legal actions, and combinations thereof;

wherein the fourth program code for presenting the other entities and the subjects of interest further comprises:

program code for presenting only ones of the other entities and ones of the subjects of interest in the Activity-based connection diagram that have relationship activity metrics with the at least one entity that meets the set of resolution filters; and

wherein the fifth program code for presenting the connections among the nodes further comprises:

program code for presenting, based on the relationship activity metrics, connections among the nodes presenting only connections between the at least one entity and ones of the other entities, and connections between the at least one entity and ones of the subjects of interest in the Activity-based connection diagram that have relationship activity metrics that meets the set of resolution filters.

26. The computer program product of claim 21, wherein the third program code for determining relationship activity metrics for the at least one entity further comprises:

program code for calculating a strength of the connections based on a rule set, wherein the rule set includes one or more rules selected from the group consisting of a rule using a number of connections, a rule using a frequency of interactions, a rule using a length of interactions, a rule using a tone of interactions, a rule using a density of interaction, a rule using a geographic proximity, a rule using pricing sheets, a rule using a feature and technical specification, a rule leveraging social media information, and a rule leveraging expected interaction compared to measured interaction.