RECOMMENDER SYSTEM BASED ON EXPERT OPINIONS

• US 20110137726A1
• Filed: 12/03/2009
• Published: 06/09/2011
• Est. Priority Date: 12/03/2009
• Status: Abandoned Application

• Current Assignee: Telefonica SA
• Original Assignee: Telefonica SA
• Inventors: Kwak, Haewoon, Amatriain, Xavier, Lathia, Neal, Pujol, Josep M., Rodriguez, Pablo
• Application Number:
  US12/630,606
• Publication Number:
  US 20110137726A1
• Time in Patent Office: Days
• US Class Current: 705/14.52
• CPC Class Codes: G06N 5/045 Explanation of inference; Explainable artificial intelligence [XAI]; Interpretable artificial intelligence
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0254 based on statistics

Abstract

The invention refers to a method and system for recommending items of interest to a target and more particularly to a recommender system predicting user interest based on expert opinions.

Claims

1. A method for recommending one or more available items to a target user u, comprising the steps of:

obtaining a set of ratings for a plurality of available items from a group of expert users E={e₁, . . . , e_k};

computing, using a computer system, a similarity measure between a target user u and an expert e according to the following equation;

2. Method according to claim 1, which further comprises:

defining a confidence threshold τ

as the minimum number of experts who must have rated item i in order to trust their prediction;

determining a subset E″

={e₁, . . . , e_n} of the set of experts E′

, E″

E′

, which includes the experts who have rated item i; and

,

if the number n of experts in the subset E″

is equal or above said confidence threshold τ

, the predicted rating r_ui computed according to equation [3] is returned;

if the number n of experts in the subset E″

is less than said confidence threshold τ

, no prediction can be made and the mean rating σ

_u for that user is returned.

3. Method according to any of claims 1-2, wherein the set of ratings for a plurality available items is obtained from item evaluations from trusted sources and use a rating inference model.

4. Method according to any of claims 1-2, wherein the set of ratings for a plurality available items is obtained using an automatic expert detection model.

5. Method according to any of claims 1-2, wherein the set of ratings for a plurality available items is obtained manually, maintaining a database of dedicated experts.