Methods and apparatus for personalized content presentation

• US 20040068552A1
• Filed: 06/26/2003
• Published: 04/08/2004
• Est. Priority Date: 12/26/2001
• Status: Abandoned Application

• Current Assignee: The Trustees of Dartmounth College (Dartmouth College)
• Original Assignee: The Trustees of Dartmounth College (Dartmouth College)
• Inventors: Rus, Daniela, Marmaros, David, Artz, John C., Kotz, David
• Application Number:
  US10/250,449
• Publication Number:
  US 20040068552A1
• Time in Patent Office: Days
• US Class Current: 709/218
• CPC Class Codes: H04L 65/1101 Session protocols
• CPC Class Codes: H04L 65/612 for unicast
• CPC Class Codes: H04L 67/04 specially adapted for terminals or networks with limited capabilities; specially adapted for terminal portability
• CPC Class Codes: H04L 67/289 Intermediate processing functionally located close to the data consumer application, e.g. in same machine, in same home or in same sub-network
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04L 67/52 specially adapted for the location of the user terminal
• CPC Class Codes: H04L 67/54 Presence management, e.g. monitoring or registration for receipt of user log-on information, or the connection status of the users
• CPC Class Codes: H04L 67/55 Push-based network services
• CPC Class Codes: H04L 67/567 Integrating service provisioning from a plurality of service providers
• CPC Class Codes: H04L 67/568 Storing data temporarily at an intermediate stage, e.g. caching
• CPC Class Codes: H04L 69/329 in the application layer [OSI layer 7]

Abstract

Methods and structure for dynamically tailoring selection of rich content for recommendation to a user wherein the recommendation process determines recommendations in accordance with past user selections. A server process (102) provides lists of recommended content to a client process (100), through a WAN (104), associated with an identified user. The user on the client process (100) then selects content and provides the server process (102) with a rating through the user feedback input (112).

Claims

1. A system for content delivery comprising:

a communication medium (104);

a client component (100) coupled to said communication medium for presenting received content to a user wherein said client component includes;

a selection component (112) for permitting a user of said client component to select received content to be presented; and

a feedback component (112) to communicate the selections to a server component; and

a server component (102) coupled to said communication medium for delivering content to said client component wherein said server component includes;

a personalization component (122) for recommending content for delivery to an identified user of said client component in response to information received from said feedback component.

2. The system of claim 1 wherein said client component further includes:

a cache memory (108) for storing said received content for later selection and presentation.

3. The system of claim 1 wherein said client component further includes:

a global positioning system (110) component to identify a present location of said client component,

wherein said selection component includes;

a location selection (112, 110) component for selecting from said received content based upon said present location of said client component.

4. The system of claim 1 wherein said client component is a Web browser and wherein said feedback component communicates with said server component via said communication medium using Hypertext Transfer Protocols (106, 116).

5. The system of claim 1 wherein said client component is operable within a portable computing device.

6. The system of claim 5 wherein said communication medium is a wireless communication medium.

7. The system of claim 1 wherein said received content comprises identification information for recommended content.

8. The system of claim 7 wherein said selection component selects recommended content based upon said identification information and requests delivery of the selected recommended content from said server component.

9. The system of claim 1 wherein said server component further includes:

a user authentication component (124) for authenticating the identity of a user of said client component.

10. The system of claim 1 wherein said personalization component includes:

a utility estimation component (226, FIGS. 6 and

     7) for estimating the utility of available content wherein said utility estimation component includes utility estimation based upon said information received from said feedback component; and

a selector component (226, FIGS. 6 and

     7) to select recommended content for said identified user based on the estimated utility of said available content.

11. The system of claim 10 wherein said utility estimation component includes:

a similarity graph computation component (226 FIGS. 6 and

     7) for determining a similarity graph representing utility of content as a multi-dimensional vector space model.

12. The system of claim 11 wherein said selector component includes:

a similarity selector (708) that selects content based on a cosine metric of vectors in said vector space model.

13. A method operable in a server process for content selection and delivery to a client process comprising the steps of:

selecting recommended content for an identified user of said client process based upon utility information represented as a multi-dimensional similarity graph vector space model (226, FIGS. 6 and

     7);

communicating said recommended content to said client process for selection by said user (226);

receiving feedback information from said client process regarding said user'"'"'s selection of content from said recommended content (228, 234); and

updating said utility information based on said feedback information (230, 236).

14. The method of claim 13 wherein said utility information includes location information and wherein said feedback information includes said location information corresponding to said identified user (220).

15. The method of claim 13 further comprising the steps of:

sending the selected content to said client process in response to receipt of said feedback information (232).

16. The method of claim 13 wherein the step of selecting includes the steps of:

computing a user similarity value to identify content selected by similar user to said identified user (226, FIGS. 6 and

     7); and

computing a content similarity value to identify content similar to preferences of said identified user (226, FIGS. 6 and

     7).

17. The method of claim 16 wherein the step of selecting further includes the step of:

combining said user similarity value and said content similarity value to identify content to be recommended to said identified user.

18. The method of claim 13 further comprising the step of:

caching said recommended content in a memory associated with said client process for later presentation to said user of said client process.