Method and system for estimating response to token instance of interest

• US 20130103624A1
• Filed: 10/20/2012
• Published: 04/25/2013
• Est. Priority Date: 10/20/2011
• Status: Active Grant

• Current Assignee: Affectomatics ltd.
• Original Assignee: Affectomatics ltd.
• Inventors: Thieberger, Gil
• Granted Patent: US 9,015,084 B2
• Time in Patent Office: Days
• US Class Current: 706/12
• CPC Class Codes: G06F 18/214 Generating training patterns; Bootstrap methods, e.g. bagging or boosting
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06N 5/046 Forward inferencing; Production systems
• CPC Class Codes: G06Q 10/063 Operations research, analysis or management
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Estimating a response to a token instance of interest, including the steps of: receiving token instances to which a user was exposed, receiving a total response of the user to the token instances; receiving attention levels of the user in the token instances; selecting the token instance of interest from among the token instances based on the attention level; and estimating the response to the token instance of interest from the total response.

Claims

1. A system configured to estimate a response to a token instance of interest, comprising:

a memory configured to store;

token instances to which a user was exposed, a total response of the user to the token instances, and at least two respective representations of attention level of the user in at least two of the token instances;

wherein the at least two of the token instances have overlapping instantiation periods;

a processor configured to utilize the representations of attention level for selecting the token instance of interest from among the at least two of the token instances; and

the processor is further configured to estimate the response to the token instance of interest from the total response.

2. The system of claim 1, wherein the total response is based on affective response values.

3. The system of claim 1, wherein the total response is based on values of a user measurement channel of the user.

4. The system of claim 1, wherein the total response is proportional to difference between the responses of the user before and after the user was exposed to the token instances.

5. The system of claim 1, wherein the memory is further configured to store a baseline value for response of the user, and the processor is further configured to calculate the total response with respect to the baseline value.

6. The system of claim 1, wherein more than 90% of the total response is attributed to the response to the token instance of interest.

7. The system of claim 1, wherein more than 50% of the total response is attributed to the response to the token instance of interest.

8. The system of claim 1, wherein the token instances originate from multiple distinct token sources.

9. The system of claim 1, wherein the response to the token instance of interest is response of the user to the token instance of interest.

10. A method for estimating a response to a token instance of interest, comprising:

receiving token instances to which a user was exposed;

receiving a total response of the user to the token instances;

receiving at least two representations of attention level of the user in at least two of the token instances;

wherein the at least two of the token instances have overlapping instantiation periods;

selecting the token instance of interest from among the at least two of the token instances based on the representations of attention level; and

estimating the response to the token instance of interest from the total response.

11. The method of claim 10, wherein the total response of the user to the token instances is based on affective response values.

12. The method of claim 10, wherein the total response of the user to the token instances is based on user measurement channels of the user.

13. The method of claim 10, wherein the total response of the user to the token instances is proportional to difference between the responses of the user before and after the user was exposed to the token instances.

14. The method of claim 10, further comprising receiving a baseline value for response of the user, and calculating the response of the user to the token instances with respect to the baseline value.

15. The method of claim 10, wherein more than 90% of the total response is attributed to the response to the token instance of interest.

16. The method of claim 10, wherein more than 50% of the total response is attributed to the response to the token instance of interest.

17. The method of claim 10, wherein the token instances originate from multiple distinct token sources.

18. The method of claim 17, wherein the token instances are detected by the user using essentially different sensory pathways.

19. The method of claim 10, wherein the response to the token instance of interest is response of the user to the token instance of interest.

20. The method of claim 10, wherein the representations of attention level are predicted based on the token instances.