Distributed system for facilitating exchange of user information and opinion using automated collaborative filtering

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.