Abstract: A system and method of providing personalized item recommendations in a communication system comprising a server and a plurality of client devices. At the server, a plurality of user rating vectors are received from a plurality of client devices and aggregated into a rating matrix that is factorized into a user feature matrix and an item feature matrix, with the product of the user feature and item feature matrixes approximating the user rating matrix. The factorization comprises the steps of the ALS1 or the IALS1 algorithm including: initializing the user feature matrix and the item feature matrix with predefined initial values; alternately optimizing the user feature matrix and the item feature matrix until a termination condition is met. The item feature matrix is transmitted from the server to at least one client device, and a predictive rating vector is generated as the product of the associated user feature vector and the item feature matrix.
Type:
Grant
Filed:
July 29, 2011
Date of Patent:
March 18, 2014
Assignee:
Gravity Research and Development Kft.
Inventors:
István Pilászy, Domonkos Tikk, Gábor Takács, András Németh Bottyán, Dávid Zibriczky
Abstract: A system and method of providing personalized item recommendations in a communication system comprising a server and a plurality of client devices. At the server, a plurality of user rating vectors are received from a plurality of client devices and aggregated into a rating matrix that is factorized into a user feature matrix and an item feature matrix, with the product of the user feature and item feature matrixes approximating the user rating matrix. The factorization comprises the steps of the ALS1 or the IALS1 algorithm including: initializing the user feature matrix and the item feature matrix with predefined initial values; alternately optimizing the user feature matrix and the item feature matrix until a termination condition is met. The item feature matrix is transmitted from the server to at least one client device, and a predictive rating vector is generated as the product of the associated user feature vector and the item feature matrix.
Type:
Application
Filed:
July 29, 2011
Publication date:
February 2, 2012
Applicant:
Gravity Research & Development Kft.
Inventors:
István Pilászy, Domonkos Tikk, Gábor Takács, András Németh Bottyán, Dávid Zibriczky