Distributed system for facilitating exchange of user information and opinion using automated collaborative filtering
First Claim
1. Client-server based apparatus for recommending an item to one of a plurality of users situated at a client computer, the client computer connected to a server computer, wherein the item has not yet been rated by the one user, the apparatus comprising:
- (A) the server computer having a first memory associated therewith, wherein the server;
(A1) stores a user profile, in the first memory, for each of a plurality of users, wherein the user profile comprises a separate rating value, supplied by a particular one of the users, for each corresponding one of a plurality of items, said items including the item non-rated by the user;
(A2) stores an item profile, in the first memory, for each of the rated items, comprises a separate rating value, for a particular one of the items, provided by each one of the plurality of the users, wherein the user profile and the item profile are distinct from each other; and
(A3) in response to a request issued by the client computer, accesses rating information from the user and item profiles stored in the first memory and provides the rating information to the client computer; and
(B) the client computer comprising;
(B1) a processor; and
(B2) a second memory, connected to the processor, for storing computer executable instructions therein; and
(B3) wherein the processor, in response to the executable instructions;
(B3a) issues, in response to interaction with the one user, the request to the server computer for the rating information;
(B3b) calculates, for each one of the plurality of users and in response to the rating information received from the server computer, a plurality of similarity factors, between said each one user and at least one other one of the users, for each of said items, including said non-rated item;
(B3c) selects, in response to the plurality of similarity factors and for each one of the plurality of users, a plurality of neighboring ones of the users, such that each of the neighboring ones of the users has an associated similarity factor which is greater than a first predefined threshold value or, if a confidence factor is associated with the associated similarity factor, both the associated similarity factor is less the first predefined threshold and the confidence factor exceeds a second predefined threshold value;
(B3d) assigns a corresponding weight to each of the neighboring users so as to define a plurality of weights; and
(B3e) recommends at least one of a plurality of the items to said one user in response to the plurality of weights and ratings given to the non-rated item by the neighboring ones of the users.
3 Assignments
0 Petitions
Accused Products
Abstract
A system for facilitating exchange of user information and opinion using automated collaborative filtering includes memory elements for storing item profiles and user profiles. The data contained in those profiles is used to calculate a number of similarity factors representing how closely the preferences of one user correlate with another. The similarity factors are evaluated to select a set of neighboring users for each user which represents the set of users which most closely correlate with a particular user. The system assigns a weight to each one of the neighboring users. The system uses the ratings given to items by those neighboring users to recommend an item to a user. The system may be distributed, i.e. the system may include a number of nodes connected to a central server. The central server includes a memory element for storing user profile data and the nodes may be the type of system described above.
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Citations
11 Claims
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1. Client-server based apparatus for recommending an item to one of a plurality of users situated at a client computer, the client computer connected to a server computer, wherein the item has not yet been rated by the one user, the apparatus comprising:
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(A) the server computer having a first memory associated therewith, wherein the server; (A1) stores a user profile, in the first memory, for each of a plurality of users, wherein the user profile comprises a separate rating value, supplied by a particular one of the users, for each corresponding one of a plurality of items, said items including the item non-rated by the user; (A2) stores an item profile, in the first memory, for each of the rated items, comprises a separate rating value, for a particular one of the items, provided by each one of the plurality of the users, wherein the user profile and the item profile are distinct from each other; and (A3) in response to a request issued by the client computer, accesses rating information from the user and item profiles stored in the first memory and provides the rating information to the client computer; and (B) the client computer comprising; (B1) a processor; and (B2) a second memory, connected to the processor, for storing computer executable instructions therein; and (B3) wherein the processor, in response to the executable instructions; (B3a) issues, in response to interaction with the one user, the request to the server computer for the rating information; (B3b) calculates, for each one of the plurality of users and in response to the rating information received from the server computer, a plurality of similarity factors, between said each one user and at least one other one of the users, for each of said items, including said non-rated item; (B3c) selects, in response to the plurality of similarity factors and for each one of the plurality of users, a plurality of neighboring ones of the users, such that each of the neighboring ones of the users has an associated similarity factor which is greater than a first predefined threshold value or, if a confidence factor is associated with the associated similarity factor, both the associated similarity factor is less the first predefined threshold and the confidence factor exceeds a second predefined threshold value; (B3d) assigns a corresponding weight to each of the neighboring users so as to define a plurality of weights; and (B3e) recommends at least one of a plurality of the items to said one user in response to the plurality of weights and ratings given to the non-rated item by the neighboring ones of the users. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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Specification