Methods and systems for selecting and presenting content based on user preference information extracted from an aggregate preference signature

• US 7,739,280 B2
• Filed: 03/06/2007
• Issued: 06/15/2010
• 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.
• Primary Examiner(s): Trujillo; James
• Assistant Examiner(s): Philips; Albert
• Application Number:
  US11/682,695
• Publication Number:
  US 20070266026A1
• Time in Patent Office: 1,197 Days
• Field of Search: 707/728, 707/734, 707/780, 707/765
• US Class Current: 707/734
• 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 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 a shared input device;

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

receiving from the shared 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 shared input device, wherein the shared input device used by the plurality of users is a solitary input device used by each user of the plurality of users so that the composite set of preferred descriptive terms collectively describes the descriptive terms associated with content items selected by each of the users of the plurality;

inferring preferences of individual users of the plurality of users of the shared input device 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;

subsequent to learning the composite set of preferred descriptive terms of the plurality of users, receiving at least one content item selection action from one of the individual users and selecting an individual set of preferred descriptive terms for use in subsequent content item selections based on comparing said at least one selected content item to the individual sets of preferred descriptive terms;

in response to receiving subsequent incremental input from the shared input device, selecting and ordering a collection of content items based on the individual set of preferred descriptive terms selected for use in subsequent content item selections; and

presenting the ordered collection of content items on a display device.

2. The method of claim 1, wherein the demographic information is at least one of age and gender.

3. The method of claim 1, further comprising inferring at least one of ages of the users, genders of the users, and number of users of the plurality of users of the shared input device based on a comparison of the composite set of preferred descriptive terms to the prespecified statistical models of preferences of a population according to demographic information.

4. The method of claim 1, wherein the prespecified statistical models of preferences of a population according to demographic information include television viewing preferences of a population according to at least one of age and gender of members of the population.

5. The method of claim 1, further comprising inferring which individual user entered the subsequent incremental input based on comparing the subsequent incremental input to the individual sets of preferred descriptive terms, wherein the act of selecting and ordering the collection of content items is based on the individual set of preferred descriptive terms corresponding to the inferred individual user.

6. The method of claim 1, further comprising:

inferring which individual user entered the subsequent incremental input based on comparing descriptive terms associated with a subsequent content item selection to the individual sets of preferred descriptive terms; and

in response to receiving incremental input entered after the subsequent incremental input, selecting and ordering a second collection of content items based on the individual set of preferred descriptive terms corresponding to the inferred individual user.

7. The method of claim 1, wherein the selecting and ordering the collection of content items is further based on popularity values associated with the content items, each popularity value indicating a relative measure of a likelihood that the corresponding content item is desired by the user.

8. The method of claim 1, wherein the set of content items includes at least one of television program items, movie items, audio/video media items, music items, contact information items, personal schedule items, web content items, and purchasable product items.

9. The method of claim 1, wherein the set of content items includes at least one of television program items, movie items, and audio/video media items and the descriptive terms includes at least one of title, cast, director, content description, and keywords associated with the content.

10. The method of claim 1, wherein the set of content items is contained on at least one of a cable television system, a video-on-demand system, an IPTV system, and a personal video recorder.

11. The method of claim 1, wherein at least one of the incremental input and the subsequent incremental input are entered by the user on an input constrained device.

12. The method of claim 11, wherein the input constrained device has a plurality of overloaded keys, each of the overloaded keys representing two or more characters.

13. The method of claim 1, wherein at least one of the incremental input and the subsequent incremental input are entered by the user on at least one of a telephone, a PDA, a computer, and a remote control.

14. The method of claim 1, wherein the presenting the ordered collection of content items on a display device includes presenting the collection of content items on at least part of a television screen.

15. The method of claim 1, wherein the presenting the ordered collection of content items on a display device includes presenting the collection of content items on a display constrained device.

16. The method of claim 15, wherein the display constrained device is at least one of a telephone, a PDA, and a remote control.

17. The method of claim 1, wherein at least one of the incremental input and the subsequent incremental input comprises at least one prefix of a word for describing the desired content items.

18. The method of claim 17, wherein at least one of the incremental input and the subsequent incremental input comprises at least two prefixes of a phrase for describing the desired content items.

19. The method of claim 1, wherein at least one of receiving incremental inputs, presenting the corresponding subset of content items, receiving selection actions, analyzing the descriptive terms, inferring preferences of individual users of the shared input device, and selecting and ordering the collection of content items is performed on a server system remote from the user.

20. The method of claim 1, wherein at least one of receiving incremental inputs, presenting the corresponding subset of content items, receiving selection actions, analyzing the descriptive terms, inferring preferences of individual users of the shared input device, and selecting and ordering the collection of content items is performed on a user client device.

21. The method of claim 1, wherein at least one the individual sets of preferred descriptive terms is stored on a user client device and selecting and ordering the collection of content items includes selecting and ordering content items stored on the client device.

22. The method of claim 1, further comprising:

organizing the content items of the set of content items into groupings based on the informational content of the content items;

determining a context in which the selection actions are performed, the context including at least one of geographic location of the input device, day, date, and time, and the group into which the selected content items are organized; and

associating the contexts of the selection actions with at least one of the individual sets of preferred content items from the composite set of preferred descriptive terms learned from the content item selections;

wherein only individual preferences associated with the context in which the individual entered the subsequent incremental input are used in the selecting and ordering of the collection of content items.

23. The method of claim 1, wherein said decomposition act is performed with no explicit designation of which individual user of the plurality of users of the shared input device performed selection actions of content items.