Patent ID: 7685232

Claim:
A method of providing personalized recommendations to anonymous users, comprising: at a server, factorizing a rating matrix, denoted by M R , into a user feature matrix, denoted by M U , and an item feature matrix, denoted by M I , wherein the rows of M R correspond to a plurality of users, the columns of M R correspond to a plurality of items, each of the cells of M R represents a rating associated with a corresponding item for a corresponding user, and M R =M U ×M I , and transmitting the item feature matrix, M I , to selected ones of a plurality of client devices associated with the plurality of users; and at one of the selected ones of the plurality of client devices associated with one of the plurality of users, calculating a user feature vector, denoted by V U , based on the item feature matrix, M I , and a rating vector, denoted by V R , wherein each of the cells of V R represents a rating associated with a corresponding one of the plurality of items for the one user, and V R =V U ×M I .