Methods and Systems for Selecting and Presenting Content Based on Context Sensitive User Preferences

• US 20100325111A1
• Filed: 09/01/2010
• Published: 12/23/2010
• Est. Priority Date: 03/06/2006
• Status: Active Grant

• Current Assignee: Veveo LLC (Xperi Inc.)
• Original Assignee: Veveo, Inc. (Adeia Inc.)
• Inventors: RAMAKRISHNAN, Kajamalai G., RAJASEKHARAN, Ajit, ARAVAMUDAN, Murali
• Granted Patent: US 8,429,188 B2
• Time in Patent Office: Days
• US Class Current: 707/737
• CPC Class Codes: G06F 16/152 using file content signatures, e.g. hash values
• 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 21/4524 : involving the geographical location of the client retrieval from the Internet by querying based on geographical locations G06F16/9537; systems specially adapted for using geographical information in broadcast systems H04H60/70; protocols in which the network application is adapted for the location of the user terminal in communication control or processing H04L67/52; services making use of the location of users or terminals in wireless networks H04W4/02; locating users or terminals in wireless networks H04W64/00
• 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 context-sensitive learned user preferences is provided. The method includes providing a set of content items having descriptive terms. The method includes receiving user input for identifying items and, in response thereto, presenting a subset of items. The method includes receiving user selections of said items and analyzing the descriptive terms of those items to learn the user'"'"'s content preferences. The method includes determining the context in which the user performed the selections and associating those contexts with the user content preferences learned from the corresponding user selections. The method includes, in response to subsequent user input, determining a context of said subsequent input and selecting and ordering a collection of items based on comparing those items'"'"' descriptive terms with the user'"'"'s learned content preferences associated with the determined context in which the user entered the subsequent input.

Claims

1. A computer implemented user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on analyzing user selections of content items to learn the content preferences of the user according to a context within which the user selected the content and using the learned content preferences to select and order subsequent user content search results when the user is within the same context, the method comprising:

providing access to a set of content items, each content item having at least one associated descriptive term to describe the content item, the content items of the set being organized into categories of related content items;

receiving incremental input entered by the user for incrementally identifying desired content items of the set, wherein the incremental input includes at least one character in a series of characters;

in response to each character of the incremental input entered by the user, presenting a subset of content items of the set to the user;

receiving actions from the user selecting content items of the subset;

analyzing the descriptive terms of the selected content items to learn content preferences of the user;

determining the context in which the user performed the selection actions, the context including at least one of;

geographic location of the user, date, day, time, and the category of the selected content items;

associating the determined contexts of the user selection actions with the user content preferences learned from the corresponding user selections;

in response to receiving subsequent incremental input entered by the user, determining a context of said subsequent incremental input and selecting and ordering a collection of content items from the set based on a comparison of the descriptive terms of the content items of the collection with the learned content preferences of the user associated with the determined context in which the user entered the subsequent incremental input; and

presenting said collection of content items to the user on a display screen.