Abstract: A computer network implemented peer forum system and method enabling question and answer rates to be increased by automatically routing questions and receiving answers to and from peers. Information is input into network via a user interface. A peer forum system enables users to ask and answer questions. A forums database captures questions and answers provided via the peer forum system. A stage database pulls and stores questions from the forums database. A question router pulls the questions from the stage database and finds peers who can answer the questions using a peer search module that uses implicit and explicit user profiles to determine the best subject matter experts to answer the questions. A set of throttle rules is associated with the question router for determining if a peer is eligible to answer a question. A delivery system delivers a communication to eligible peers requesting an answer to the question.

Abstract: A networked peer and item recommendation system makes recommendations to users such as documents of interest and peers with whom the users may want to connect. User profile information is maintained in a profiles database. A log enables the collection of user behavior information. A cluster filtering algorithm determines a cluster that a querying user belongs to. A collaborative filtering algorithm locates other users having implicit and explicit profiles in the database that are similar to the profile of the querying user. A dynamic expert verification algorithm is associated with the collaborative filtering algorithm to verify the qualifications of users and produce bias towards users with higher quality interactions. A search engine returns items based on a keyword provided by the querying user. A sorting algorithm sorts the items returned by the cluster filtering algorithm, collaborative filtering algorithm and search engine for presentation to the querying user.

Abstract: A networked peer and item recommendation system makes recommendations to users such as documents of interest and peers with whom the users may want to connect. User profile information is maintained in a profiles database. A log enables the collection of user behavior information. A cluster filtering algorithm determines a cluster that a querying user belongs to. A collaborative filtering algorithm locates other users having implicit and explicit profiles in the database that are similar to the profile of the querying user. A dynamic expert verification algorithm is associated with the collaborative filtering algorithm to verify the qualifications of users and produce bias towards users with higher quality interactions. A search engine returns items based on a keyword provided by the querying user. A sorting algorithm sorts the items returned by the cluster filtering algorithm, collaborative filtering algorithm and search engine for presentation to the querying user.

Abstract: A computer network implemented peer forum system and method enabling question and answer rates to be increased by automatically routing questions and receiving answers to and from peers. Information is input into network via a user interface. A peer forum system enables users to ask and answer questions. A forums database captures questions and answers provided via the peer forum system. A stage database pulls and stores questions from the forums database. A question router pulls the questions from the stage database and finds peers who can answer the questions using a peer search module that uses implicit and explicit user profiles to determine the best subject matter experts to answer the questions. A set of throttle rules is associated with the question router for determining if a peer is eligible to answer a question. A delivery system delivers a communication to eligible peers requesting an answer to the question.

Abstract: A system is provided for locating peers having a desired expertise. User profile information is stored in a profiles database. A search engine indexes the profiles database and appends appropriate profile tags to this information. A peer relevancy algorithm searches for candidate peers among the indexed user profile information. Weights are assigned to candidate peers based on different categories of the indexed user profile information, and peer matches are selected based on the assigned weights. In order to provide matches that are most likely to accept a connection request, data is maintained as to which potential peers have a history of accepting requests to connect and which have a history of refusing to connect. Potential matches are biased to favor those that have a tendency to accept connection requests. Contact information of requester and recipients are not disclosed until the recipient accepts the requester's connection request.

Abstract: A networked peer and item recommendation system makes recommendations to users such as documents of interest and peers with whom the users may want to connect. User profile information is maintained in a profiles database. A log enables the collection of user behavior information. A cluster filtering algorithm determines a cluster that a querying user belongs to. A collaborative filtering algorithm locates other users having implicit and explicit profiles in the database that are similar to the profile of the querying user. A search engine returns items based on a keyword provided by the querying user. A sorting algorithm sorts the items returned by the cluster filtering algorithm, collaborative filtering algorithm and search engine for presentation to the querying user. Potential peers are also presented to the querying user. The items and potential peers presented are those most likely to be of help to the querying user.

Abstract: A system is provided for locating peers having a desired expertise. User profile information is stored in a profiles database. A search engine indexes the profiles database and appends appropriate profile tags to this information. A peer relevancy algorithm searches for candidate peers among the indexed user profile information. Weights are assigned to candidate peers based on different categories of the indexed user profile information, and peer matches are selected based on the assigned weights. In order to provide matches that are most likely to accept a connection request, data is maintained as to which potential peers have a history of accepting requests to connect and which have a history of refusing to connect. Potential matches are biased to favor those that have a tendency to accept connection requests. Contact information of requester and recipients are not disclosed until the recipient accepts the requester's connection request.