Patent ID: 9704102
Date: 2017-07-11
CPC Classifications: G06N,G09B

Claim:
1. A computer-implemented method comprising: receiving input data that includes response data, wherein the response data includes a set of preference values that have been assigned to content items by content users, wherein the content items are content items that have been viewed or accessed or used by the content users, wherein the preference values are drawn from a universe of possible values, wherein said receiving is performed by a computer system; computing output data based on the input data using a first latent factor model, wherein said computing is performed by the computer system, wherein the output data includes at least: an association matrix that defines a set of K concepts associated with the content items, wherein K is smaller than the number of the content items, wherein, for each of the K concepts, the association matrix defines the concept by specifying strengths of association between the concept and the content items; and a concept-preference matrix including, for each content user and each of the K concepts, an extent to which the content user prefers the concept, wherein a row or column of the content-preference matrix is used to predict one or more content items which the corresponding content user is likely to have an interest in; displaying, via a display device, a visual representation of at least a subset of the association strengths in the association matrix, wherein said displaying the visual representation includes displaying a graph based on the association matrix, wherein the graph depicts the strengths of association between at least a subset of the content items and at least a subset of the K concepts.