COGNITIVE BIAS DETERMINATION AND MODELING

• US 20160260341A1
• Filed: 03/06/2015
• Published: 09/08/2016
• Est. Priority Date: 03/06/2015
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Pandey, Suraj, Baughman, Aaron K., Kozloski, James R., Lynar, Timothy M., Wagner, John M.
• Granted Patent: US 10,109,214 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G09B 5/00 Electrically-operated educational appliances working with questions and answers G09B7/00; simulators G09B9/00; advertising or displaying in general G09F
• 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

In an approach for determining a preferred learning style of the user, a computer receives user information of a user. The computer collects data for user model development, wherein data includes actions performed by the user. The computer creates one or more associations between actions in the collected data for user model development and received user information. The computer determines a preferred learning style of the user based on the created one or more associations.

Claims

1. A method for determining a preferred learning style of the user, the method comprising:

receiving, by one or more computer processors, user information of a user;

collecting, by one or more computer processors, data for user model development, wherein data includes actions performed by the user;

creating, by one or more computer processors, one or more associations between actions in the collected data for user model development and received user information; and

determining, by one or more computer processors, a preferred learning style of the user based on the created one or more associations.

2. The method of claim 1, further comprising:

determining, by one or more computer processors, a user model from one or more existing user models that is associated with the received user information;

applying, by one or more computer processors, the determined user model to modify information displayed to the user; and

wherein the user model from one or more existing user models modifies the presentation of information to the user comprising on one of more of;

learning styles, user preferences, user information, user states, features, and relationships between content and users based on source application, content, and destination application information as provided through actions performed by the user.

3. The method of claim 1, wherein receiving user information further comprises:

receiving, by one or more computer processors, user information that comprises one or more of demographic information and public information;

wherein the demographic information includes at least one of;

an age range, a gender, an education level, and a profession associated with the user; and

wherein the public information includes at least one of comprises a job role, a job title, a department, and a peer group associated with the user.

4. The method of claim 2, wherein determining the user model from the one or more existing user models that is associated with the received user information further comprises:

determining, by one or more computer processors, whether the received user information matches stored existing user information associated with a user model from the one or more existing user models; and

responsive to determining the received user information matches stored existing user information associated with the user model from the one or more existing user models, retrieving, by one or more computer processors, a user model associated with the stored existing user information that matches the received user information.

5. The method of claim 2, wherein determining the user model from the one or more existing user models that is associated with the received user information further comprises:

determining, by one or more computer processors, whether the received user information matches stored existing user information associated with a user model from the one or more existing user models;

responsive to determining the received user information does not match stored existing user information associated with the user model from the one or more existing user models, determining, by one or more computer processor, stored existing user information that is similar to the received user information; and

selecting, by one or more computer processors, a user model that is associated with the determined existing user information that is similar.

6. The method of claim 1, wherein collecting data for user model development further comprises:

gathering, by one or more computer processors, the actions performed by the user and information associated with the actions, wherein the actions include copying, cutting, and pasting the information on a clipboard;

determining, by one or more computer processors, the information from a first user action that is placed on the clipboard;

storing, by one or more computer processors, the determined information placed on the clipboard and application software associated with the first user action;

determining, by one or more computer processors, information that is transferred from the clipboard through a second user action; and

storing, by one or more computer processors, the determined information and application software associated with the second user action.

7. The method of claim 1, wherein determining a preferred learning style of the user based on the created one or more associations further comprises:

extracting, by one or more computer processors, features from the collected data;

identifying, by one or more computer processors, salient topics from the extracted features; and

applying, by one or more computer processors, a density model to the identified salient topics to determine learning styles.

8. A computer program product for determining a preferred learning style of the user, the computer program product comprising:

one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, the program instructions comprising;

program instructions to receive user information of a user;

program instructions to collect data for user model development, wherein data includes actions performed by the user;

program instructions to create one or more associations between actions in the collected data for user model development and received user information; and

program instructions to determine a preferred learning style of the user based on the created one or more associations.

9. The computer program product of claim 8, further comprises program instructions, stored on the one or more computer readable storage media, to:

determine a user model from one or more existing user models that is associated with the received user information;

apply the determined user model to modify information displayed to the user; and

wherein the user model from one or more existing user models modifies the presentation of information to the user comprising on one of more of;

learning styles, user preferences, user information, user states, features, and relationships between content and users based on source application, content, and destination application information as provided through actions performed by the user.

10. The computer program product of claim 8, wherein receiving user information further comprises program instructions, stored on the one or more computer readable storage media, to:

receive user information that comprises one or more of demographic information and public information;

wherein the demographic information includes at least one of;

an age range, a gender, an education level, and a profession associated with the user; and

wherein the public information includes at least one of comprises a job role, a job title, a department, and a peer group associated with the user.

11. The computer program product of claim 9, wherein determining the user model from the one or more existing user models that is associated with the received user information further comprises program instructions, stored on the one or more computer readable storage media, to:

determine whether the received user information matches stored existing user information associated with a user model from the one or more existing user models; and

responsive to determining the received user information matches stored existing user information associated with the user model from the one or more existing user models, retrieve a user model associated with the stored existing user information that matches the received user information.

12. The computer program product of claim 9, wherein determining the user model from the one or more existing user models that is associated with the received user information further comprises program instructions, stored on the one or more computer readable storage media, to:

determine whether the received user information matches stored existing user information associated with a user model from the one or more existing user models;

responsive to determining the received user information does not match stored existing user information associated with the user model from the one or more existing user models, determine stored existing user information that is similar to the received user information; and

select a user model that is associated with the determined existing user information that is similar.

13. The computer program product of claim 8, wherein collecting data for user model development further comprises program instructions, stored on the one or more computer readable storage media, to:

gather the actions performed by the user and information associated with the actions, wherein the actions include copying, cutting, and pasting the information on a clipboard;

determine the information from a first user action that is placed on the clipboard;

store the determined information placed on the clipboard and application software associated with the first user action;

determine information that is transferred from the clipboard through a second user action; and

store the determined information and application software associated with the second user action.

14. The computer program product of claim 8, wherein determining a preferred learning style of the user based on the created one or more associations further comprises program instructions, stored on the one or more computer readable storage media, to:

extract features from the collected data;

identify salient topics from the extracted features; and

applying a density model to the identified salient topics to determine learning styles.

15. A computer system for determining a preferred learning style of the user, the computer system comprising:

one or more computer processors, one or more computer readable storage media, and program instructions stored on the computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising;

program instructions to receive user information of a user;

program instructions to collect data for user model development, wherein data includes actions performed by the user;

program instructions to create one or more associations between actions in the collected data for user model development and received user information; and

program instructions to determine a preferred learning style of the user based on the created one or more associations.

16. The computer system of claim 15, further comprises program instructions, stored on the one or more computer readable storage media, to:

determine a user model from one or more existing user models that is associated with the received user information;

apply the determined user model to modify information displayed to the user; and

wherein the user model from one or more existing user models modifies the presentation of information to the user comprising on one of more of;

learning styles, user preferences, user information, user states, features, and relationships between content and users based on source application, content, and destination application information as provided through actions performed by the user.

17. The computer system of claim 16, wherein determining the user model from the one or more existing user models that is associated with the received user information further comprises program instructions, stored on the one or more computer readable storage media, to:

determine whether the received user information matches stored existing user information associated with a user model from the one or more existing user models; and

responsive to determining the received user information matches stored existing user information associated with the user model from the one or more existing user models, retrieve a user model associated with the stored existing user information that matches the received user information.

18. The computer system of claim 16, determining the user model from the one or more existing user models that is associated with the received user information further comprises program instructions, stored on the one or more computer readable storage media, to:

determine whether the received user information matches stored existing user information associated with a user model from the one or more existing user models;

responsive to determining the received user information does not match stored existing user information associated with the user model from the one or more existing user models, determine stored existing user information that is similar to the received user information; and

select a user model that is associated with the determined existing user information that is similar.

19. The computer system of claim 15, wherein collecting data for user model development further comprises program instructions, stored on the one or more computer readable storage media, to:

gather the actions performed by the user and information associated with the actions, wherein the actions include copying, cutting, and pasting the information on a clipboard;

determine the information from a first user action that is placed on the clipboard;

store the determined information placed on the clipboard and application software associated with the first user action;

determine information that is transferred from the clipboard through a second user action; and

store the determined information and application software associated with the second user action.

20. The computer system of claim 15, wherein determining a preferred learning style of the user based on the created one or more associations further comprises program instructions, stored on the one or more computer readable storage media, to:

extract features from the collected data;

identify salient topics from the extracted features; and

applying a density model to the identified salient topics to determine learning styles.