Methods, apparatus, and computer program products for estimating a mood of a user, using a mood of a user for network/service control, and presenting suggestions for interacting with a user based on the user's mood

• US 7,728,735 B2
• Filed: 12/04/2007
• Issued: 06/01/2010
• Est. Priority Date: 12/04/2007
• Status: Expired due to Fees

• Current Assignee: At&T Delaware Intellectual Property, Inc. (AT&T, Inc.)
• Original Assignee: AT&T Intellectual Property I LP (AT&T, Inc.)
• Inventors: Aaron, Jeffrey, Streijl, Robert C.
• Primary Examiner(s): TWEEL JR, JOHN ALEXANDER
• Application Number:
  US11/949,943
• Publication Number:
  US 20090140864A1
• Time in Patent Office: 910 Days
• Field of Search: 340/573.1, 340/539.12, 340/539.22, 340/539.26, 340/539.14, 340/522
• US Class Current: 340/573.1
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

A mood of a user is estimated based on a user'"'"'s profile, data indicative of a user'"'"'s mood received from a communication device associated with the user and from sources other than the user, and environmental data with a potential impact on the user'"'"'s mood. Data indicative of the user'"'"'s mood and the environmental data are processed to filter out data that is not relevant to the user'"'"'s mood. The filtered data is cross-correlated with the user profile, and the mood of the user is estimated based on the cross-correlated filtered data. A network and services may be controlled based on a user'"'"'s mood. Suggestions for interacting with the user may be generated based on the user'"'"'s mood.

Claims

1. A method for estimating a mood of a user, comprising:

receiving a user profile;

receiving data indicative of a user'"'"'s mood from a communication device associated with the user;

receiving data indicative of the user'"'"'s mood from at least one source other than the user;

receiving environmental non-user specific data with a potential impact on the user'"'"'s mood;

processing the data from the communication device and sources other than the user and the environmental data to filter out data that is not relevant to the user'"'"'s mood;

cross-correlating the filtered data with the user profile; and

estimating the mood of the user based on the cross-correlated filtered data.

2. The method of claim 1, further comprising:

determining a relevancy metric for the cross-correlated data based on rules;

comparing the relevancy metric of the cross-correlate data to a relevancy threshold;

filtering out data with a relevancy metric falling below the relevancy threshold, wherein the mood of the user is estimated based on the data having a relevancy metric that meets or surpasses the relevancy threshold; and

generating a mood metric based on the filtered data.

3. The method of claim 2, wherein the relevancy threshold differs among users.

4. The method of claim 2, wherein the relevancy metric differs among users.

5. The method of claim 1, wherein the data indicative of the user'"'"'s mood includes at least one of series and scripts, volume and stress indicators in voice, indicators and patterns in written input, keywords, phrases, user selections, user actions, and user responses.

6. An apparatus for estimating a mood of a user, comprising:

an input for receiving a user profile, receiving data indicative of a user'"'"'s mood from at least one communication device associated with the user, receiving data indicative of the user'"'"'s mood from sources other than the user, and receiving environmental data with a potential impact on the user'"'"'s mood; and

a processor for processing the collected data to filter data that is not relevant to the user'"'"'s mood, cross-correlating the filtered data with the user profile, and estimating the mood of the user based on the cross-correlated filtered data.

7. The apparatus of claim 5, wherein the processor determines a relevancy metric for the cross-correlated data, compares the relevancy metric of the cross-correlate data to a relevancy threshold, and filters out data with a relevancy metric falling below the relevancy threshold, wherein the mood of the user is estimated based on the data having a relevancy metric that meets or surpasses the relevancy threshold.

8. The apparatus of claim 7 wherein the relevancy threshold differs among users.

9. The apparatus of claim 7, wherein the relevancy metric differs among users.

10. The apparatus of claim 5, wherein the data indicative of the user'"'"'s mood includes at least one of series and scripts, volume and stress indicators in voice, indicators and patterns in written input, keywords, phrases, user selections, user actions, and user responses.

11. A computer program product for estimating a mood of a user, comprising a computer usable medium having a computer readable program, wherein the computer readable program includes instructions that, when executed on a computer, cause the computer to:

receive a user profile;

receive data indicative of a user'"'"'s mood from a communication device associated with the user;

receive data indicative of the user'"'"'s mood from sources other than the user;

receive environmental data with a potential impact on the user'"'"'s mood;

process the collected data to filter data that is not relevant to the user'"'"'s mood;

cross-correlate the filtered data with the user profile; and

estimate the mood of the user based on the cross-correlated filtered data.

12. The computer program product of claim 11, wherein the computer program further includes instructions that, when executed on the computer, cause the computer to:

determine a relevancy metric for the cross-correlated data;

compare the relevancy metric of the cross-correlate data to a relevancy threshold; and

filter out data with a relevancy metric falling below the relevancy threshold, wherein the mood of the user is estimated based on the data having a relevancy metric that meets or surpasses the relevancy threshold.

13. The computer program product of claim 12, wherein the relevancy threshold differs among users.

14. The computer program product of claim 12, wherein the relevancy metric differs among users.

15. The computer program product of claim 11, wherein the data indicative of the user'"'"'s mood includes at least one of series and scripts, volume and stress indicators in voice, indicators and patterns in written input, keywords, phrases, user selections, user actions, and user responses.