Patent Abstract:
An online social network is managed using one server for database management tasks and another server, preferably in a distributed configuration, for CPU-intensive computational tasks, such as finding a shortest path between two members or a degree of separation between two members. The additional server has a memory device containing relationship information between members of the online social network and carries out the CPU-intensive computational tasks using this memory device. With this configuration, the number of database lookups is decreased and processing speed is thereby increased.

Full Description:
BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     The present invention generally relates to a system and method for managing an online social network, and more specifically, to a system and method for managing information exchange between members of an online social network. 
     2. Description of the Related Art 
     Online social networking sites have been rapidly gaining in popularity, and operators of online social networking sites have been adding servers and switches to their infrastructure to keep up with the increasing demand. Keeping up with the increasing demand has, however, proved to be difficult for two reasons. First, online social networking sites are virally marketed, as current members actively solicit nonmembers to sign up and join the network, and as a result, its growth has been very rapid. Second, the load on the social networking site is dependent not only on the total number of members but also on the total number of relationships. Because a member typically has multiple relationships, this means that the load increase associated with each new member is much greater than typical. 
     SUMMARY OF THE INVENTION 
     The present invention deals with the system load demands by improving the processing efficiencies of the online social networking site. The improvement in the processing efficiencies is achieved by providing one or more graph servers to be used in combination with the site&#39;s application server. The application server is configured to handle database management tasks, and the graph servers are configured to handle CPU-intensive computational tasks. 
     More specifically, the application server manages a database that contains member profile information and member relationship information. The graph servers keep track of how the members are socially connected to one another (hereinafter referred to as, “social network map”) in a dedicated memory device, and process and respond to queries from the application server using the social network map stored in the dedicated memory device. The social network map that is stored in the dedicated memory device of the graph servers is updated to reflect any changes to the member relationship information that are made in the database. 
     Because the present invention processes relationship information using a social network map that is stored in a dedicated memory device, the number of database lookups is decreased and an improvement in the processing speed is achieved. Depending on the number of relationships that are tracked, a dramatic improvement in the processing speed might be achieved with the present invention. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a diagram that conceptually represents the relationships between members in a social network; 
         FIG. 2  is a block diagram illustrating the system for managing an online social network according to an embodiment of the present invention; 
         FIG. 3  is a sample adjacency list that is maintained by the graphs servers of the present invention; 
         FIG. 4  is a flow diagram illustrating the method for processing a request by one member to view the profile of another member in the system of  FIG. 2 ; 
         FIG. 5  is a flow diagram illustrating the method for determining whether a member can be contacted by another member in the system of  FIG. 2 ; and 
         FIG. 6  is a flow diagram illustrating the method for processing a search request in the system of  FIG. 2 . 
     
    
    
     DETAILED DESCRIPTION 
     A social network is generally defined by the relationships among groups of individuals, and may include relationships ranging from casual acquaintances to close familial bonds. A social network may be represented using a graph structure. Each node of the graph corresponds to a member of the social network. Edges connecting two nodes represent a relationship between two individuals. In addition, the degree of separation between any two nodes is defined as the minimum number of hops required to traverse the graph from one node to the other. A degree of separation between two members is a measure of relatedness between the two members. 
       FIG. 1  is a graph representation of a social network centered on a given individual (ME). Other members of this social network include A-U whose position, relative to ME&#39;s, is referred to by the degree of separation between ME and each other member. Friends of ME, which includes A, B, and C, are separated from ME by one degree of separation (1 d/s). A friend of a friend of ME is separated from ME by 2 d/s. As shown, D, E, F and G are each separated from ME by 2 d/s. A friend of a friend of a friend of ME is separated from ME by 3 d/s.  FIG. 1  depicts all nodes separated from ME by more than 3 degrees of separation as belonging to the category ALL. 
     Degrees of separation in a social network are defined relative to an individual. For example, in ME&#39;s social network, H and ME are separated by 2 d/s, whereas in G&#39;s social network, H and G are separated by only 1 d/s. Accordingly, each individual will have their own set of first, second and third degree relationships. 
     As those skilled in the art understand, an individual&#39;s social network may be extended to include nodes to an Nth degree of separation. As the number of degrees increases beyond three, however, the number of nodes typically grows at an explosive rate and quickly begins to mirror the ALL set. 
       FIG. 2  is a block diagram illustrating a system for managing an online social network. As shown,  FIG. 2  illustrates a computer system  100 , including an application server  200  and distributed graph servers  300 . The computer system  100  is connected to a network  400 , e.g., the Internet, and accessible over the network by a plurality of computers, which are collectively designated as  500 . 
     The application server  200  manages a member database  210 , a relationship database  220  and a search database  230 . The member database  210  contains profile information for each of the members in the online social network managed by the computer system  100 . The profile information may include, among other things: a unique member identifier, name, age, gender, location, hometown, a pointer to an image file, listing of interests, attributes, etc. The profile information also includes VISIBILITY and CONTACTABILITY settings, the uses of which are described below in connection with  FIGS. 4 and 5 . 
     The relationship database  220  stores member relationship information in the following format: (MemberID — 1, MemberID — 2, Time, Add/Delete). MemberID — 1 and MemberID — 2 identify the two members whose relationship is defined by this input. Time is a variable corresponding to the time stamp of this input. Add/Delete is a variable indicating whether the friendship between MemberID — 1 and MemberID — 2 is to be added or deleted. 
     In addition, the contents of the member database  210  are indexed and optimized for search, and stored in the search database  230 . The member database  210 , the relationship database  220 , and the search database  230  are updated to reflect inputs of new member information and edits of existing member information that are made through the computers  500 . 
     The member database  210 , the relationship database  220 , and the search database  230  are depicted separately in the block diagram of  FIG. 2  to illustrate that each performs a different function. The databases  210 ,  220 ,  230  may each represent a different database system, module, or software; or any two of the three or all three may be parts of the same database system, module, or software. 
     The application server  200  also manages the information exchange requests that it receives from the remote computers  500 . The information exchange requests may be a request to view a member&#39;s profile ( FIG. 4 ), a request to send messages to a member ( FIG. 5 ), or a search request ( FIG. 6 ). The application server  200  relies on the distributed graph servers  300  to process certain CPU-intensive tasks that are part of the information exchange request. The graph servers  300  receive a query from the application server  200 , process the query and return the query results to the application server  200 . 
     The graph servers  300  have a dedicated memory device  310 , such as a random access memory (RAM), in which an adjacency list that reflects the member relationship information is stored. A sample adjacency list that reflects the social network map of  FIG. 1  is shown in  FIG. 3 . A list item is generated for each member and contains a member identifier for that member and member identifier(s) corresponding to friend(s) of that member. As an alternative to the adjacency list, an adjacency matrix or any other graph data structure may be used. 
     The graph servers  300 , on a fixed interval, e.g., every five minutes, check the relationship database  220  for any incremental changes to the member relationship information. If there is, e.g., if (current time—5 minutes) is less than or equal to the time stamp corresponding to an entry in the relationship database  220 , the adjacency list stored in the dedicated memory device  510  is updated to reflect such incremental change. If a friendship is to be added, the adjacency list item for MemberID — 1 is amended to add MemberID — 2 and the adjacency list item for MemberID — 2 is amended to add MemberID — 1. If a friendship is to be deleted, the adjacency list item for MemberID — 1 is amended to delete MemberID — 2 and the adjacency list item for MemberID — 2 is amended to delete MemberID — 1. Alternatively, the adjacency list can be updated in real time, i.e., synchronously with the updates to the relationship database  220 . 
     The queries processed by the graph servers  300  include:
         List_of_Members (M 1 , N d/s), which returns a list of member identifiers of all members who are exactly N d/s from member M 1 ;   No_of_Members (M 1 , N d/s), which returns a raw number indicating the number of members who are exactly N d/s from member M 1 ;   Get_Network (M 1 , N d/s), which returns a list of member identifiers of all members that are within N d/s from member M 1 ;   Shortest_Path (M 1 , M 2 ), which returns the shortest path, if any, between member M 1  and member M 2  (the shortest path is displayed in the form of member identifiers of those members disposed in the shortest path between member M 1  and member M 2 ); and   Are_Connected? (M 1 , M 2 , degrees), which returns the degree of separation corresponding to the shortest path between member M 1  and member M 2 , if the two are connected. If the two are not connected, an error code indicating that the two members are not connected is returned.       

     For the calculation of the shortest path in the queries listed above, any of the shortest path algorithms for a node network defined by an adjacency list may be used, e.g., breadth first search algorithm. The algorithms for carrying out other calculations that are necessary to process the queries listed above are programmed using conventional techniques. 
     In  FIG. 2 , a plurality of distributed graph servers  300  are depicted, and is preferred over a single graph server because the distributed structure permits resources to be shared. However, the present invention may also be practiced with a single graph server. 
     The application server  200  and the graphs servers  300  are depicted separately in the block diagram of  FIG. 2  to illustrate that the two are performing separate processes. The application server  200  and the graphs servers  300  may be housed within a single physical structure, or they may be parts of a single processor that is programmed to carry out their separate processes in parallel. 
       FIG. 4  is a flow diagram illustrating the method for processing a request by one member (e.g., M 1 ) to view the profile of another member (e.g., M 2 ) in the system of  FIG. 2 . In Step  610 , the application server  200  receives a request by member M 1  to view the profile of member M 2 . As an example, this happens when member M 1  clicks on a hyperlink associated with member M 2 . The full profile of member M 2  will be displayed if the d/s between M 1  and M 2  is less than or equal to the VISIBILITY setting set by member M 2  or if the VISIBILITY setting set by member M 2  is ALL. (VISIBILITY setting may be set at 1, 2, 3 or ALL.) Otherwise, only the mini-profile of member M 2  will be displayed. In Step  620 , the application server  200  retrieves M 2 &#39;s VISIBILITY setting from the member database  210 . If M 2 &#39;s VISIBILITY setting is ALL, the full profile of M 2  will be transmitted to M 1  for display at M 1 &#39;s computer (Steps  630  and  640 ). If not, the application server  200  sends the Are_Connected? query to the graph servers  300  to determine the d/s between member M 1  and member M 2  (Steps  630  and  650 ). The graph servers  300  execute this query and return the d/s that it computed to the application server  200 . If the computed d/s is greater than the VISIBILITY setting or if member M 1  and member M 2  are not connected, the mini-profile of member M 2  and a message indicating that member M 2 &#39;s full profile can only be viewed by members in his or her personal network is transmitted to M 1  for display at M 1 &#39;s computer (Steps  660  and  670 ). Otherwise, the full profile of member M 2  is transmitted to M 1  for display at M 1 &#39;s computer (Steps  660  and  640 ). 
       FIG. 5  is a flow diagram illustrating the method for determining whether a member can be contacted by another member in the system of  FIG. 2 . In the example given herein, it is assumed that member M 1  is attempting to send a message to member M 2 . In Step  710 , the application server  200  retrieves the CONTACTABILITY setting of member M 2 . (CONTACTABILITY setting may be set as 1, 2, 3 or ALL.) If M 2 &#39;s CONTACTABILITY setting is ALL, this means that member M 2  is permitting contact from anyone, and consequently, when member M 1  views member M 2 &#39;s profile, a “Send Message” hyperlink will appear through which member M 1  will be able to send messages to member M 2  (Steps  720  and  730 ). If M 2 &#39;s CONTACTABILITY setting is not set to ALL, the application server  200  sends the Are_Connected? query to the graph servers  300  to determine the d/s between member M 1  and member M 2  (Steps  720  and  740 ). The graph servers  300  execute this query and return the d/s that it computed to the application server  200 . If the computed d/s is greater than the CONTACTABILITY setting or if member M 1  and member M 2  are not connected, this means that member M 2  is not permitting contact from member M 1  and the “Send Message” hyperlink will not be displayed when member M 1  views member M 2 &#39;s profile (Steps  750  and  760 ). If the computed d/s is less than or equal to the CONTACTABILITY setting, this means that member M 2  is permitting contact from member M 1 , and consequently, when member M 1  views M 2 &#39;s profile, a “Send Message” hyperlink will appear through which member M 2  will be able to send messages to member M 1  (Steps  750  and  730 ). 
       FIG. 6  is a flow diagram illustrating the method for processing a search request in the system of  FIG. 2 . In Step  810 , the application server  200  receives a search query input by member M 1 . The search query is divided into two parts. The first part specifies search terms for pre-selected categories such as gender, age, interests and location. The second part specifies a d/s setting, which may be set at 1, 2, 3 or ALL. For example, the search query may be: [gender (female), age (less than 30), d/s (at most 2)]. The first part of this search query is [gender (female), age (less than 30)] and the second part of this search query is [d/s (at most 2)]. In Step  820 , the application server  200  issues the first part of the search query to the search database  230  to obtain member identifiers for those members whose profiles meet the specified criteria. In Step  830 , the application server  200  issues a Get_Network query to the graph servers  300  to obtain a list of member identifiers of all members that are within the d/s specified in the second part of the search query. The application server  200  merges the results from the search database  230  and the graph servers  300  (Step  840 ), and transmits the merged results to member M 1  (Step  850 ). After the merged results are delivered to member M 1 , the member may click on any of the results to view that member&#39;s profile and, if the “Send Message” hyperlink is displayed, attempt to send a message to that member through that hyperlink. 
     While particular embodiments according to the invention have been illustrated and described above, it will be clear that the invention can take a variety of forms and embodiments within the scope of the appended claims.

Technology Classification (CPC): 6