Methods and Systems for Selecting and Presenting Content Based on User Preference Information Extracted from an Aggregate Preference Signature

• US 20100241625A1
• Filed: 06/07/2010
• Published: 09/23/2010
• Est. Priority Date: 03/06/2006
• Status: Active Grant

• Current Assignee: Veveo, Inc. (Adeia Inc.)
• Original Assignee: Veveo, Inc. (Adeia Inc.)
• Inventors: Aravamudan, Murali, Rajasekharan, Ajit, Ramakrishnan, Kajamalai G.
• Granted Patent: US 8,073,848 B2
• Time in Patent Office: Days
• US Class Current: 707/734
• CPC Class Codes: G06F 16/2453 Query optimisation
• CPC Class Codes: G06F 16/2457 with adaptation to user needs
• CPC Class Codes: G06F 16/24575 using context
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/2462 Approximate or statistical queries
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/284 Relational databases
• CPC Class Codes: G06F 16/335 Filtering based on additional data, e.g. user or group profiles filtering in web context G06F16/9535, G06F16/9536
• CPC Class Codes: G06F 16/337 Profile generation, learning or modification
• CPC Class Codes: G06F 16/435 Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06F 16/437 Administration of user profiles, e.g. generation, initialisation, adaptation, distribution
• CPC Class Codes: G06F 16/438 Presentation of query results
• CPC Class Codes: G06F 16/686 using information manually generated, e.g. tags, keywords, comments, title or artist information, time, location or usage information, user ratings
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9538 Presentation of query results
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06Q 30/0205 Location or geographical consideration
• CPC Class Codes: H04N 21/44222 Analytics of user selections, e.g. selection of programs or purchase activity monitoring of user selections in data processing systems G06F11/34; arrangements for monitoring the user's behaviour or opinions in broadcast systems H04H60/33
• CPC Class Codes: H04N 21/44224 Monitoring of user activity on external systems, e.g. Internet browsing
• CPC Class Codes: H04N 21/4532 : involving end-user characteristics, e.g. viewer profile, preferences monitoring of user activities for profile generation for accessing a video database G06F16/739; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18
• CPC Class Codes: H04N 21/466 : Learning process for intelligent management, e.g. learning user preferences for recommending movies services using the results of monitoring in broadcast systems H04H60/61
• CPC Class Codes: H04N 21/4828 : for searching program descriptors retrieval of video data G06F16/739
• CPC Class Codes: Y10S 707/99933 : Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99934 : Query formulation, input preparation, or translation
• CPC Class Codes: Y10S 707/99937 : Sorting
• CPC Class Codes: Y10S 707/99943 : Generating database or data structure, e.g. via user interface
• CPC Class Codes: Y10S 707/99945 : Object-oriented database structure processing

Abstract

A method of selecting and presenting content based on inferred user preferences is provided. The method includes providing a set of content items having associated descriptive terms and receiving search inputs from an input device and presenting a corresponding subset of content items. The method includes receiving selection actions of content items and analyzing the descriptive terms associated with the selected content items to learn a composite set of preferred descriptive terms of the plurality of users of the input device. The method includes inferring preferences of individual users from the composite set of preferred descriptive terms by decomposing the composite set of preferred descriptive terms into individual sets of preferred descriptive terms. The decomposition act utilizes prespecified statistical models of preferences. The method includes, in response to receiving subsequent user search input, selecting and ordering a collection of content items based on the inferred preferences of said individual user.

Claims

1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on inferring preferences of a given user from a plurality of users of an input device, the preferences of the plurality of users of the input device being learned based on content items selected by the plurality of users, the method comprising:

providing a set of content items, each content item having at least one associated descriptive term to describe the content item;

receiving incremental inputs from an input device;

in response to said incremental input, presenting a corresponding subset of content items;

receiving from the input device selection actions of content items;

analyzing the descriptive terms associated with the selected content items to learn a composite set of preferred descriptive terms of the plurality of users of the input device;

inferring preferences of individual users of the plurality of users from the composite set of preferred descriptive terms by decomposing the composite set of preferred descriptive terms into individual sets of preferred descriptive terms, said decomposition act utilizing prespecified statistical models of preferences of a population according to demographic information; and

in response to receiving subsequent incremental input entered by one of the individual users, selecting and ordering a collection of content items based on the inferred preferences of said individual user.