METHOD AND SYSTEM FOR AUTOMATED CONTENT CUSTOMIZATION AND DELIVERY

• US 20100075289A1
• Filed: 09/19/2008
• Published: 03/25/2010
• Est. Priority Date: 09/19/2008
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Kattaya, Mohamed M.M.M., Maher, Ahmed E.I., Yassin, Amr F.
• Application Number:
  US12/234,322
• Publication Number:
  US 20100075289A1
• Time in Patent Office: Days
• US Class Current: 434/323
• CPC Class Codes: G09B 7/00 Electrically-operated teaching apparatus or devices working with questions and answers mechanically operated G09B3/00; computing arrangements G06F

Abstract

A method and system for automated customization of original content for one or more users, is provided. One implementation involves obtaining behavior information for a user, profiling the user based on the user behavior information, determining a preferred learning style for the user based on the user profiling, and customizing the original content based on the preferred learning style for the user. Profiling the user may involve analyzing the user behavior information using one or more profiling patterns for profiling the user to determine scores for different behavior categories for the user. Customizing the original content may involve determining a preferred learning style for the user based on the user profiling further includes selecting a customization scheme from a scheme repository, based on said scores for different behavior categories for the user, and applying the selected customization scheme to the original content to generated customized content for the user.

Claims

1. An automated method of customizing original content for one or more users, comprising:

obtaining behavior information for a user;

profiling the user based on the user behavior information;

determining a preferred learning style for the user based on the user profiling; and

customizing the original content based on the preferred learning style for the user.

2. The method of claim 1, wherein profiling the user based on the user behavior information further includes analyzing the user behavior information using one or more profiling patterns for profiling the user to determine scores for different behavior categories for the user.

3. The method of claim 2, wherein profiling the user further includes analyzing the user behavior information using a Neural Language Processing (NLP) pattern for profiling the user to determine scores for different behavior categories for the user.

4. The method of claim 2, wherein profiling the user further includes analyzing the user behavior information using a Whole Brain Thinking (WBT) pattern for profiling the user to determine scores for different behavior categories for the user.

5. The method of claim 2, wherein customizing the original content further includes:

determining a preferred learning style for the user based on the user profiling further includes selecting a customization scheme from a scheme repository, based on said scores for different behavior categories for the user; and

applying the selected customization scheme to the original content to generated customized content for the user.

6. The method of claim 5, wherein the customized content is geared to preferred learning style for the user.

7. The method of claim 1 further including providing the customized electronic content to the user via the Internet.

8. The method of claim 1, wherein obtaining user behavior information includes obtaining user behavior information by sensing one or more of:

user visual behavior, user linguistic behavior, user social preference behavior, and user logic orientation behavior.

9. A computer program product for customizing original content for one or more users, comprising a computer usable medium including a computer readable program including program instructions, wherein the computer readable program when executed on a computer causes the computer to:

profile a user based on user behavior information for the user;

determine a preferred learning style for the user based on the user profiling; and

customize the original content based on the preferred learning style for the user.

10. The computer program product of claim 9, further including instructions to cause the computer to:

analyze the user behavior information using one or more profiling patterns for profiling the user to determine scores for different behavior categories for the user.

11. The computer program product of claim 10, further including instructions to cause the computer to:

analyze the user behavior information using a Natural Language Processing (NLP) pattern for profiling the user to determine scores for different behavior categories for the user.

12. The computer program product of claim 10, further including instructions to cause the computer to:

analyze the user behavior information using a Whole Brain Thinking (WBT) pattern for profiling the user to determine scores for different behavior categories for the user.

13. The computer program product of claim 10, further including instructions to cause the computer to:

selecting a customization scheme from a scheme repository based on said scores for different behavior categories for the user; and

apply the selected customization scheme to the original content to generated customized content for the user.

14. The computer program product of claim 13, wherein the customized content is geared to preferred learning style for the user.

15. The computer program product of claim 9 further including instructions to cause the computer to:

obtain behavior information via a sensor by sensing one or more of;

user visual behavior, user linguistic behavior, user social preference behavior, and user logic orientation behavior.

16. A system for customizing original content for one or more users, comprising:

one or more clients, each client representing a user;

a customization server configured for customizing original content for each of one or more clients; and

the server comprising;

a pattern recognizer configured for profiling a user based on the user behavior information;

a learning style identifier configured for determining a preferred learning style for the user based on the user profiling; and

a customizer configured for customizing the original content based on the preferred learning style for the user.

17. The system of claim 16, wherein the pattern recognizer is further configured for analyzing the user behavior information using one or more profiling patterns for profiling the user to determine scores for different behavior categories for the user.

18. The system of claim 17, wherein the pattern recognizer is further configured for analyzing the user behavior information using one or more of:

a Neural Language Processing (NLP) pattern for profiling the user to determine scores for different behavior categories for the user; and

a Whole Brain Thinking (WBT) pattern for profiling the user to determine scores for different behavior categories for the user.

19. The system of claim 17, wherein the customizer includes:

a customization selector configured for determining a preferred learning style for the user based on the user profiling further includes selecting a customization scheme from a scheme repository, based on said scores for different behavior categories for the user; and

a customization engine configured for applying the selected customization scheme to the original content to generated customized content for the user;

wherein the customized content is geared to preferred learning style for the user.

20. The system of claim 16, wherein the server comprises a web server and each client comprises a web client, capable of communicating with the web server via the Internet, such that the web server provides each customized content to a corresponding client via the Internet.