Representing user behavior information

• US 8,775,471 B1
• Filed: 07/03/2012
• Issued: 07/08/2014
• Est. Priority Date: 04/14/2005
• Status: Active Grant

• Current Assignee: AudienceScience, Inc.
• Original Assignee: AudienceScience, Inc.
• Inventors: Kozyrczak, Maciek, Chen, Cheng Che, Nayfeh, Basem
• Primary Examiner(s): LE, DEBBIE M
• Application Number:
  US13/541,660
• Time in Patent Office: 735 Days
• Field of Search: None
• US Class Current: 707/790
• CPC Class Codes: G06F 16/95 Retrieval from the web
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

A facility for analyzing user behavior information is described. The facility receives a stream, of user behavior information. The facility augments a representation of user behavior in accordance with the received stream of user behavior information. The representation augmented by the facility is a sparse matrix of user behavior facts. The facility analyzes the sparse matrix to obtain an analysis result for the received stream of user behavior.

Claims

1. A method in a computing system for analyzing user behavior information, comprising:

receiving a stream of user behavior information;

augmenting a representation of user behavior in accordance with the received stream of user behavior information, the representation comprising a sparse matrix of elements, each element containing information indicating a user behavior fact, wherein a recurring time period is indicated in connection with the representation, wherein each element of the sparse matrix identifies an instance of the recurring time period to which the user behavior fact indicated by the information contained by the element relates, and wherein each element of the sparse matrix indicates a number of times a particular user performed an action of a particular type during the identified instance of the recurring time period; and

analyzing the sparse matrix to obtain an analysis result for the stream of user behavior.

2. The method of claim 1 wherein the analyzing comprises traversing a first dimension of the sparse matrix representation at a selected position in a second dimension of the sparse matrix representation to analyze user behavior facts relating to a selected value in the second dimension that corresponds to the selected position in the second dimension.

3. The method of claim 1 wherein a first dimension of the sparse matrix corresponds to user identity and a second dimension of the sparse matrix corresponds to action type,

the method further comprising receiving a request for analysis,

wherein the analyzing is performed upon receiving the request for analysis.

4. The method of claim 1 wherein the received stream of user behavior information reflects web browsing behavior.

5. The method of claim 1 wherein the received stream of user behavior information reflects television viewing behavior.

6. The method of claim 1 wherein the received stream of user behavior information reflects audio listening behavior.

7. The method of claim 1 wherein the received stream of user behavior information reflects online product purchasing behavior.

8. The method of claim 1 wherein the received stream of user behavior information reflects online behavior.

9. A computer-readable medium whose contents cause a computing system to perform a method for analyzing user behavior information, the method comprising:

receiving a stream of user behavior information;

augmenting a representation of user behavior in accordance with the received stream of user behavior information, the representation comprising a sparse matrix of elements, each element containing information indicating a user behavior fact, wherein a recurring time period is indicated in connection with the representation, wherein each element of the sparse matrix identifies an instance of the recurring time period to which the user behavior fact indicated by the information contained by the element relates, and wherein each element of the sparse matrix indicates a number of times a particular user performed an action of a particular type during the identified instance of the recurring time period; and

analyzing the sparse matrix to obtain an analysis result for the stream of user behavior.

10. The computer-readable medium of claim 9 wherein the analyzing comprises traversing a first dimension of the sparse matrix representation at a selected position in a second dimension of the sparse matrix representation to analyze user behavior facts relating to a selected value in the second dimension that corresponds to the selected position in the second dimension.

11. The computer-readable medium of claim 9 wherein the entirety of the augmented representation of user behavior resides in volatile memory of a single computer system during the analysis.

12. The computer-readable medium of claim 9 wherein the received stream of user behavior information reflects web browsing behavior.

13. The computer-readable medium of claim 9 wherein the received stream of user behavior information reflects television viewing behavior.

14. The computer-readable medium of claim 9 wherein the received stream of user behavior information reflects audio listening behavior.

15. The computer-readable medium of claim 9 wherein the received stream of user behavior information reflects online product purchasing behavior.

16. The computer-readable medium of claim 9 wherein the received stream of user behavior information reflects online behavior.

17. One or more computer memories collectively storing a user behavior data structure, the data structure comprising a sparse matrix of elements, each element containing information indicating a user behavior fact, wherein a recurring time period is indicated in connection with the user behavior data structure, wherein each element of the sparse matrix identifies an instance of the recurring time period to which the user behavior fact indicated by the information contained by the element relates, and wherein each element of the sparse matrix indicates a number of times a particular user performed an action of a particular type during the identified instance of the recurring time period.

18. The computer memories of claim 17 wherein the sparse matrix has at least two dimensions, including a first dimension for user identity and a second dimension for action type.

19. The computer memories of claim 17 wherein, for each element of the sparse matrix, the particular user is identified by a position in a first dimension of the matrix occupied by the element, and the particular action type is identified by a position in a second dimension of the matrix occupied by the element.

20. The computer memories of claim 17 wherein the entirety of the user behavior data structure resides in volatile memory of a single computer system.