Patent Publication Number: US-11657060-B2

Title: Utilizing interactivity signals to generate relationships and promote content

Description:
BACKGROUND 
     The proliferation of computerized automation of processes in every aspect of life, data storage and processing have become a major component of networked systems handling social interactions. In such systems, social data is entered, modified, or deleted from a number of sources. The same data is maintained in multiple social data stores in same or different formats, and a social data store has to pick up or synchronize changes to social data based on changes in a different store. Various social data stores from simple tables to complicated databases are maintained and synchronized as new entries or modifications are made by different sources. Variety of relationships are built and broken many times within a short period of time between users of the social data. The changes are synchronized at regular intervals. In addition, variety of services are offered to enable internal and external parties&#39; interactivity with the social data hosted by the data stores. 
     Legacy entity relationship models are typically incomplete despite availability of many solutions for tracking attributes of users to attempt to derive relationships such as a role of a business contact. Attributes on relationships are not supported in a generic manner. Accordingly, relationships between people may not be captured, may only be captured in unstructured form, or partially captured through explicitly defined and rigid schemas. The lack of these abilities makes it difficult to present an overview of associations between users and content. 
     SUMMARY 
     This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This summary is not intended to exclusively identify key features or essential features of the claimed subject matter, nor is it intended as an aid in determining the scope of the claimed subject matter. 
     Embodiments are directed to utilization of interactivity signals to generate relationships and promote content. An analysis application may query one or more interactivity applications to retrieve interactivity signals. An interactivity signal may be an interaction pattern between a user and relations of the user that describe a relationship between the user, other users, and content. The analysis application may construct a relationship graph based on the interactivity signals. The relationship graph may chart relationships between the users associated with the interactivity signals. Next, the analysis application may promote content of a user based on the relationship graph. The content of the user may be ranked based on the relationship graph. Additionally, a weight of the interactivity signals may be adjusted to improve a ranking of the relationship graph and a ranking of the content. 
     These and other features and advantages will be apparent from a reading of the following detailed description and a review of the associated drawings. It is to be understood that both the foregoing general description and the following detailed description are explanatory and do not restrict aspects as claimed. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG.  1    is a conceptual diagram illustrating utilization of interactivity signals to generate relationships and promote content, according to embodiments; 
         FIG.  2    is a component diagram of a scheme to utilize interactivity signals to generate relationships and promote content, according to embodiments; 
         FIG.  3    illustrates examples of user interfaces displaying generated relationships and promoted content utilizing interactivity signals, according to embodiments; 
         FIG.  4    is a simplified networked environment, where a system according to embodiments may be implemented; 
         FIG.  5    is a block diagram of an example computing operating environment, where embodiments may be implemented; and 
         FIG.  6    illustrates a logic flow diagram for a process to utilize interactivity signals to generate relationship and promote content according to embodiments. 
     
    
    
     DETAILED DESCRIPTION 
     As briefly described above, interactivity signals may be utilized to generate relationships and promote content. An analysis application may construct a relationship graph based on interactivity signals queried from interactivity applications. Content of a user may be promoted based on the relationship graph. A weight of the interactivity signals may be adjusted to improve a ranking of the relationship graph and a ranking of the content. 
     In the following detailed description, references are made to the accompanying drawings that form a part hereof, and in which are shown by way of illustrations specific embodiments or examples. These aspects may be combined, other aspects may be utilized, and structural changes may be made without departing from the spirit or scope of the present disclosure. The following detailed description is therefore not to be taken in a limiting sense, and the scope of the present invention is defined by the appended claims and their equivalents. 
     While the embodiments will be described in the general context of program modules that execute in conjunction with an application program that runs on an operating system on a computing device, those skilled in the art will recognize that aspects may also be implemented in combination with other program modules. 
     Generally, program modules include routines, programs, components, data structures, and other types of structures that perform particular tasks or implement particular abstract data types. Moreover, those skilled in the art will appreciate that embodiments may be practiced with other computer system configurations, including hand-held devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, mainframe computers, and comparable computing devices. Embodiments may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices. 
     Embodiments may be implemented as a computer-implemented process (method), a computing system, or as an article of manufacture, such as a computer program product or computer readable media. The computer program product may be a computer storage medium readable by a computer system and encoding a computer program that comprises instructions for causing a computer or computing system to perform example process(es). The computer-readable storage medium is a computer-readable memory device. The computer-readable storage medium can for example be implemented via one or more of a volatile computer memory, a non-volatile memory, a hard drive, and a flash drive. 
     Throughout this specification, the term “platform” may be a combination of software and hardware components to utilize interactivity signals to generate relationships and promote content. Examples of platforms include, but are not limited to, a hosted service executed over a plurality of servers, an application executed on a single computing device, and comparable systems. The term “server” generally refers to a computing device executing one or more software programs typically in a networked environment. However, a server may also be implemented as a virtual server (software programs) executed on one or more computing devices viewed as a server on the network. More detail on these technologies and example embodiments may be found in the following description. 
       FIG.  1    includes a conceptual diagram  100  illustrating utilization of interactivity signals to generate relationships and promote content, according to embodiments. 
     An analysis application executing on a server  102  may utilize interactivity signals to generate relationships and promote content. An interactivity signal may be an interaction pattern between users. The interaction pattern may be used by the analysis application to generate a relationship between the users. A user may be a person, an item, a location, an animal, an application, and similar ones. A user may be a combination of multiple users. The interaction pattern may describe a relationship between the users and relay content between the users. In an example scenario, the analysis application may query an interactivity application to retrieve an interactivity signal between a user A, a user B, and content. The interactivity application may be an application that allows one or more interactions between the user A, the user B, and the content. The content may include a document, a message, a video clip, an audio clip, and similar ones. In addition, the interactivity signal may be an interaction pattern about a content associated with user A. The analysis application may determine a relationship between the user A and the user B based on the content referred to by the interactivity signal. The analysis application may promote the content based on the determined relationship. In the previous example, the user A and the user B are not provided as limiting examples. Other users may also use the interactivity application and partake in interactions with the user A, the user B, and the content. 
     The analysis application executing on server  102  may query interactivity applications executing on a content server  104  and a data server  106 . In an example scenario, an interactivity application executing on content server  104  may provide interactivity services to users and content. The analysis application may query the interactivity application to retrieve interactivity signals between the users and content of the interactivity application. Alternatively, the analysis application may receive the interactivity signals from the interactivity application in a push scheme. The interactivity signals may be used to generate a relationship graph to promote content associated with a user, such as a document of the user. 
     In addition, the analysis application may query an interactivity application executing on the data server  106 . The interactivity application executing on the data server  106  may store attributes of users such as contact information. The interactivity application may manage relationships between the users such as business, personal, social, and similar relationships. The interactivity application may also manage relationships based on interaction between the users. An example may include frequency of access. 
     The analysis application may retrieve the interactivity signals associated with the users from data server  106 . A relationship graph may be constructed using the interactivity signals. Alternatively, a previously constructed relationship graph may be augmented by retrieving new or updated interactivity signals. 
     The analysis application executing on the server  102  may rank content associated with a user based on the relationship graph. An example may include documents accessed by the user as content ranked by the analysis application. The content may also be sorted by the analysis application based on frequency of access by the user and relations of the user. Relations of the user may be other users. The content may be also be sorted based on a relevancy to the user and to the relations of the user. The content may be recommended to the relations based on the frequency of access. 
     The ranked content may be presented to devices  110 . The content may be transmitted to the devices  110  on demand, based on a received request from the devices  110  for the content. Alternatively, the server  102  may transmit the content to the devices based on a subscription for the content. The content may be presented to a viewer  108  through one or more user interfaces on devices  110 . The devices  110  may include a desktop computer, a tablet computer, a notebook computer, a smart phone, and similar ones. 
     While the example system in  FIG.  1    has been described with specific components including a server  102  utilizing interactivity signals to generate relationships and promote content, embodiments are not limited to these components or system configurations and can be implemented with other system configuration employing fewer or additional components. In an alternate example, the analysis application may be executed in server  102  along with the interactivity applications. The approaches discussed here may be applied to any compliance process provided by an application and/or a server using the principles described herein. 
       FIG.  2    is a component diagram of a scheme to utilize interactivity signals to generate relationships and promote content. Diagram  200  illustrates an example of an analysis application  202  generating relationships and promoting content by using interactivity signals. 
     The analysis application  202  may query an interactivity application to receive interactivity application output  204 . Alternatively, the analysis application may receive the interactivity application out  204  from the interactivity application in a push scheme based on a predetermined schedule or on demand. The interactivity application generating the interactivity application output  204  may include internal and external interactivity applications managing user, content, and relationship information. The interactivity application output  204  may be interactivity signals that include a recommendation establishing a relationship between users. The interactivity application output  204  may include interactivity signals associated with users that the analysis application is privileged to access. 
     The analysis application  202  may store interactivity signals within a signal store input  210  component. The signal store input  210  component may manage interactions with external interactivity applications including access to, query of, and retrieval of interactivity signals. The signal store input  210  component may access an interactivity application through an application programming interface (API). The API may be customized by the analysis application  202  to gain access to the interactivity signals managed by the interactivity application. Customization may include configuration of the API to establish a connection with the interactivity application. 
     Views  208  component of the analysis application  202  may be used to analyze views of content. The interactivity signals may associate the content with users. Views  208  component may analyze the interactivity signals to determine recentness of a view of the content within a predetermined period. The predetermined period may be a number of years, months, weeks, days, hours, seconds, and combinations of each. In an example scenario, the predetermined period may be assigned as a two weeks to consider the content as relevant to a user or relations of the user. The predetermined period example is not provided in a limiting sense, other time periods may be also be assigned as the predetermined period to consider the content relevant to the user or the relations. 
     People relationships  206  component may analyze interactions between the user and the relations of the user. The analysis application  202  may determine a weighted relationship between the user and the relations in response to determining a number of interactions between the user and the relations above a predetermined threshold. The predetermined threshold may be manually configured or dynamically configured based a number of criteria. Interactions may include a follow operation, a share operation, a suggestion, a collaboration, a presentation, and similar ones. The relationship may be inserted into the relationship graph. 
     Output from people relationships  206 , views  208 , and signal store input  210  components may be transmitted to a popular content  212  component for analysis. The input of the popular content  212  component may include relationships, view frequency information, and interactivity signals. The popular content  212  component may generate popular content accessed by the user and relations of the user. The popular content  212  component may generate content that may be interesting to the user based on interactions with the content by relations of the user. The relations of the user may be selected automatically or manually from a list of users derived from the interactivity signals associating the user to the relations. 
     The graph index feeder  214  component may analyze the relationships to produce a relationship graph. The graph index feeder  214  may chart the relationships into the relationship graph. Content such as documents analyzed by the popular content  212  module may be ranked based on the relationship graph. The graph index feeder  214  component may rank the content based on scores assigned to the content according to relationships associated with the content. The relationship graph and ranked content may be presented to a consumer through a graph index  216  that presents ranked content based on relationships of the consumer. 
     The analysis application  202  may use a ranking function to rank the content based on the relationship graph. According to some embodiments, following values may be used by the ranking function: 
     A value of P i S may include a related person score between a user and a related person i (also referred to as a relation). The value P i S may be computed by the people relationships  206  component. A person may be one of the users associated through a relationship as derived interactivity signals. The relationship may be ranked by the related person score in the relationship graph. 
     A value of PD i,j S may include a person-document score between person i and document j where document j is content associated with the person i. Based on the interactions by the person i on the document j. 
     A value of D j S may include a score of document j for a selected person. 
     A value off may refer to a feature used to create a score between related people and documents. An example of a feature may include a number of views of a content such as a document by a person. 
     A value of C f  may include a count of a feature such as a number of views from a person of a document. 
     A value of T f  may include a timestamp of a last time of an occurrence of a feature event on a document by a person. 
     A function φ c (C f ) may be a count of a feature function. An example feature function may include φ c (C f )=1 for all C f . However, embodiments are not limited to φ c (C f )=1 for all C f . 
     A function φ s (X) may be a feature count saturation function. 
     A function φ r (T f ) may be a recentness of a feature function. 
     A value W f  may include a feature weight. The weight may be used to adjust how a feature is to a document score. The weight of an interactivity signal may be adjusted to add a relationship or to remove a relationship from the relationship graph. Adjustment of the weight may be accomplished manually or automatically based on predetermined criteria. 
     The analysis application  202  may calculate a score of a document j for a person i with 
                   PD     i   ,   j       ⁢   S     =         φ   s     (       ∑     ∀   f       ⁢           ⁢       W   f     ⁢       φ   r     ⁡     (     T   f     )           )     ⁢       φ   c     ⁡     (     C   f     )           )         
in order to relate the document j with the selected user. Links pointing to the document from a number of users are aggregated by a function of
 
     
       
         
           
             
               
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     Since the score above is depending on the value P i S, (i.e. the score of the related person), documents from the people with higher scores are increased. Documents are sorted by relevancy when computing the scores D j S for documents j among users. 
     Feature saturation may be determined by 
                   φ   s     ⁡     (   X   )       =     X     k   +   X         ,     k   &gt;   0.           
A recentness of a feature of a document may be determined by a drop off function of: φ r (T f )=1/(1+αT f ), α&gt;0.
 
     The examples of the ranking function are not provided in a limiting sense. Other ranking functions may be used to rank the content. 
       FIG.  3    illustrates examples of user interfaces displaying generated relationships and promoted content utilizing interactivity signals, according to embodiments. 
     As shown in the diagram  300 , a client application  302  may render relationships of a user  304 . The user  304  may be represented through a graphic such as a headshot image and identifier information such as a name. A relationship to the user may be identified through relations  306 ,  308 , and  310 . The relations  306 ,  308 , and  310  may identify the relationship with the user  304  through descriptive terms for the relationship including a manager, working with, and peers. Descriptive terms are not provided in a limiting sense, other descriptive terms such as family, friends, and similar ones may be used to describe a relationship between the user and the relations. 
     The analysis application may rank content associated with the user  304  based on a relationship graphic. In response to detecting an interaction selecting one or more of the relations of the user  304 , the analysis application may rank the content associated with the user  304  and the selected relations. The ranked content may be presented to the client application  302 . The client application may display an action link  312  to render the ranked content associated with the user  304  and the selected relations. 
     In response to detecting an activation of the action link  312 , the client application  314  may display the ranked content as content  316 . The content  316  may include documents, distribution lists (i.e.: email), groups, meetings, and similar content related to the user  304  and the selected relations. In addition, interest information may be provided. The interest information may include a summary of interactions between relations of the user  304  and the content  316 . The interest information may provide a description of why the content may be interesting to the user based on the summary. The interest information may be transmitted to the client application to cause the client application to display the interest information within one or more interest panes  318  associated with the content  316 . 
     The example scenarios and schemas in  FIGS.  2  and  3    are shown with specific components, data types, and configurations. Embodiments are not limited to systems according to these example configurations. Utilizing interactivity signals to generate relationships and promote content may be implemented in configurations employing fewer or additional components in applications and user interfaces. Furthermore, the example schema and components shown in  FIGS.  2  and  3    and their subcomponents may be implemented in a similar manner with other values using the principles described herein. 
       FIG.  4    is an example networked environment, where embodiments may be implemented. A system utilizing interactivity signals to generate relationships and promote content may be implemented via software executed over one or more servers  414  such as a hosted service. The platform may communicate with client applications on individual computing devices such as a smart phone  413 , a laptop computer  412 , or desktop computer  411  (‘client devices’) through network(s)  410 . 
     Client applications executed on any of the client devices  411 - 413  may facilitate communications via application(s) executed by servers  414 , or on individual server  416 . An analysis application may generate a relationship graph from interactivity signals. The relationship graph may be used to rank content of a user. The ranked content may be promoted to the user and relations of the user based on the relationship. The relationship and content data may be stored in data store(s)  419  directly or through database server  418 . 
     Network(s)  410  may comprise any topology of servers, clients, Internet service providers, and communication media. A system according to embodiments may have a static or dynamic topology. Network(s)  410  may include secure networks such as an enterprise network, an unsecure network such as a wireless open network, or the Internet. Network(s)  410  may also coordinate communication over other networks such as Public Switched Telephone Network (PSTN) or cellular networks. Furthermore, network(s)  410  may include short range wireless networks such as Bluetooth or similar ones. Network(s)  410  provide communication between the nodes described herein. By way of example, and not limitation, network(s)  410  may include wireless media such as acoustic, RF, infrared and other wireless media. 
     Many other configurations of computing devices, applications, data sources, and data distribution systems may be employed to utilize interactivity signals to generate relationships and promote content. Furthermore, the networked environments discussed in  FIG.  4    are for illustration purposes only. Embodiments are not limited to the example applications, modules, or processes. 
       FIG.  5    and the associated discussion are intended to provide a brief, general description of a suitable computing environment in which embodiments may be implemented. With reference to  FIG.  5   , a block diagram of an example computing operating environment for an application according to embodiments is illustrated, such as computing device  500 . In a basic configuration, computing device  500  may be any computing device executing an analysis application according to embodiments and include at least one processing unit  502  and system memory  504 . Computing device  500  may also include a plurality of processing units that cooperate in executing programs. Depending on the exact configuration and type of computing device, the system memory  504  may be volatile (such as RAM), non-volatile (such as ROM, flash memory, etc.) or some combination of the two. System memory  504  typically includes an operating system  505  suitable for controlling the operation of the platform, such as the WINDOWS® operating systems from MICROSOFT CORPORATION of Redmond, Wash. The system memory  504  may also include one or more software applications such as program modules  506 , an analysis application  522 , and a relationship module  524 . 
     The analysis application  522  may query interactivity applications to retrieve interactivity signals. The analysis application  522  may generate a relationship graph from the relationships inferred in the interactivity signals. The relationship module  524  may be used to rank content associated with a user based on the relationship graph. The analysis application  522  may promote the ranked content. This basic configuration is illustrated in  FIG.  5    by those components within dashed line  508 . 
     Computing device  500  may have additional features or functionality. For example, the computing device  500  may also include additional data storage devices (removable and/or non-removable) such as, for example, magnetic disks, optical disks, or tape. Such additional storage is illustrated in  FIG.  5    by removable storage  509  and non-removable storage  510 . Computer readable storage media may include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information, such as computer readable instructions, data structures, program modules, or other data. System memory  504 , removable storage  509  and non-removable storage  510  are all examples of computer readable storage media. Computer readable storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by computing device  500 . Any such computer readable storage media may be part of computing device  500 . Computing device  500  may also have input device(s)  512  such as keyboard, mouse, pen, voice input device, touch input device, an optical capture device for detecting gestures, and comparable input devices. Output device(s)  514  such as a display, speakers, printer, and other types of output devices may also be included. These devices are well known in the art and need not be discussed at length here. 
     Computing device  500  may also contain communication connections  516  that allow the device to communicate with other devices  518 , such as over a wired or wireless network in a distributed computing environment, a satellite link, a cellular link, a short range network, and comparable mechanisms. Other devices  518  may include computer device(s) that execute communication applications, web servers, and comparable devices. Communication connection(s)  516  is one example of communication media. Communication media can include therein computer readable instructions, data structures, program modules, or other data. By way of example, and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared and other wireless media. 
     Example embodiments also include methods. These methods can be implemented in any number of ways, including the structures described in this document. One such way is by machine operations, of devices of the type described in this document. 
     Another optional way is for one or more of the individual operations of the methods to be performed in conjunction with one or more human operators performing some. These human operators need not be collocated with each other, but each can be only with a machine that performs a portion of the program. 
       FIG.  6    illustrates a logic flow diagram for a process to utilize interactivity signals to generate relationships and promote content according to embodiments. Process  600  may be implemented through an analysis application. 
     Process  600  begins with operation  610  querying one or more interactivity applications to retrieve interactivity signals. The analysis application may construct a relationship graph based on the interactivity signals at operation  620 . Content of a user may be ranked based on the relationship graph. At operation  630 , content of the user may be promoted based on the relationship graph. A weight of the interactivity signals may be adjusted to improve a ranking of the relationship graph and a ranking of the content at operation  640 . 
     According to some embodiments, a method may be provided to utilize interactivity signals to generate relationships and promote content. An example method may include querying one or more interactivity applications to retrieve interactivity signals, constructing a relationship graph based on the interactivity signals, promoting content of a user based on the relationship graph, and adjusting weight of the interactivity signals to improve a ranking of the relationship graph and a ranking of the content. 
     According to other embodiments, the method may include retrieving new or updated interactivity signals from the one or more interactivity applications, and augmenting the relationship graph with the new or updated interactivity signals. The content may be ranked based on the relationship graph. The content may be sorted based on a relevancy to the user and relations associated with the content. Alternatively, the content may be sorted based on a frequency of access by the user and a frequency of access by relations associated with content. Additionally, the documents may be analyzed as the content. 
     According to further embodiments, the method may include presenting the relationship graph and the content in a graph index. The documents as the content may be ranked based on a person-document score assigned to the documents. The person-document score may be assigned based on an association of the documents with the user and relations of the user. A relationship may be determined from one or more of the interactivity signals by computing a related person score between the user and a related person derived from the interactivity signals. The relationship may be ranked within the relationship graph based on the related person score. 
     According to some embodiments, a computing device ( 500 ) may be provided to utilize interactivity signals to generate relationships and promote content. The computing device may include a memory, a processor coupled to the memory. The processor may execute an analysis application in conjunction with instructions stored in the memory. The analysis application may be configured to query one or more interactivity applications to retrieve interactivity signals, construct a relationship graph based on the interactivity signals, promote content of a user by ranking the content based on the relationship graph, and adjust weight of the interactivity signals to improve a ranking of the relationship graph and a ranking of the content. 
     According to other embodiments, the analysis application may be further configured to analyze interactions between the user and relations of the user to determine a relationship from the interactivity signals. The relationship may be determined in response to determining a number of the interactions above a predetermined threshold, and the relationship may be inserted into the relationship graph. An application programming interface (API) may be customized to establish a connection to the one or more interactivity applications to retrieve the interactivity signals. A recentness of a view of the content may be determined within a predetermined period by the user or relations of the user by analyzing the interactivity signals. The predetermined period may be assigned as two weeks to consider the content as relevant to the user or the relations. 
     According to some embodiments, a computer-readable memory device may be provided to utilize interactivity signals to generate relationships and promote content. The instructions may cause a method to be performed in response to execution, the method being similar to the methods described above. 
     The operations included in process  600  are for illustration purposes. An analysis application may be implemented by similar processes with fewer or additional steps, as well as in different order of operations using the principles described herein. 
     The above specification, examples and data provide a complete description of the manufacture and use of the composition of the embodiments. Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims and embodiments.