Bi-model recommendation engine for recommending items and peers
First Claim
1. A peer and item recommendation system implemented on a digital computer network for making recommendations to a querying user, comprising:
- a user interface enabling user profile information to be entered and stored in a profiles database; and
a collaborative filtering algorithm associated with said database, said collaborative filtering algorithm;
(a) locating other users having profiles in said database based on a similarity among the profiles of the querying user and the other users based on at least one of explicit and implicit profiles,(b) locating other users based on those who have the most expertise for a keyword provided by the querying user,(c) determining scores of the other users located in steps (a) and (b) indicative of how well said other users match said querying user,(d) locating items used by a best matching subset of the other users located in steps (a) and (b) based on said scores, and(e) returning the items located in step (d) for consideration by the querying user.
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Accused Products
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.
90 Citations
24 Claims
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1. A peer and item recommendation system implemented on a digital computer network for making recommendations to a querying user, comprising:
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a user interface enabling user profile information to be entered and stored in a profiles database; and a collaborative filtering algorithm associated with said database, said collaborative filtering algorithm; (a) locating other users having profiles in said database based on a similarity among the profiles of the querying user and the other users based on at least one of explicit and implicit profiles, (b) locating other users based on those who have the most expertise for a keyword provided by the querying user, (c) determining scores of the other users located in steps (a) and (b) indicative of how well said other users match said querying user, (d) locating items used by a best matching subset of the other users located in steps (a) and (b) based on said scores, and (e) returning the items located in step (d) for consideration by the querying user. - View Dependent Claims (7, 8, 9, 10, 11, 12, 15)
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2. A peer and item recommendation system in accordance with claim comprising:
a cluster filtering algorithm for identifying clusters of users based on item consumption patterns, where users consuming the same kinds of items belong to the same clusters, said cluster filtering algorithm; (i) locating other users in said database who belong to the same cluster as a querying user, (ii) locating items associated with said keyword and used by the other users in the same cluster, and (iii) returning the items located in step (ii) for consideration by the querying user. - View Dependent Claims (3, 4, 5, 6, 13, 14)
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16. A method for recommending peers and/or items such as documents, events, search keywords and alert keywords to querying users, comprising:
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providing a user interface enabling user profile information to be entered and stored in a profiles database; locating other users in said database that are similar to the profile of a querying user based on at least one of explicit and implicit profiles, locating, other users in said database that have the most expertise for a keyword provided by the querying user, determining scores of the other users located indicative of how well said other users match said querying user, based on said scores, locating items used by a best matching subset of the other users located, and returning the items located on the basis of the best matching subset for consideration by the querying user. - View Dependent Claims (17, 18, 19, 20, 21, 22, 23, 24)
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Specification