Generating a recommendation to add a member to a receptivity cohort

• US 8,954,433 B2
• Filed: 02/22/2012
• Issued: 02/10/2015
• Est. Priority Date: 12/16/2008
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Angell, Robert Lee, Friedlander, Robert R., Kraemer, James R.
• Primary Examiner(s): ALAM, SHAHID AL
• Application Number:
  US13/402,586
• Publication Number:
  US 20120150790A1
• Time in Patent Office: 1,084 Days
• Field of Search: 707/736, 707/E17.143, 707/702, 707/705, 707/803, 709/207, 709/206, 706/45, 706/54, 706/55, 705/7.37
• US Class Current: 707/736
• CPC Class Codes: G06F 16/284 Relational databases
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06Q 10/10 Office automation; Time management

Abstract

A processor-implemented method, system, and/or computer program product generate a recommendation to add a member to a receptivity cohort. A receptivity cohort is made up of members who share a conduct attribute, which is a facial expression, body language, and/or social interaction of a person. The conduct attribute has been predetermined to be an indicator of a level of receptiveness to a proposed future change in a set of circumstances. Biometric sensor data, which describe the facial expression, body language and/or social interaction for a candidate member, are retrieved from a set of biometric sensors. The retrieved biometric sensor data for the candidate member is compared to the conduct attribute of members of the receptivity cohort. In response to the biometric sensor data for the candidate member matching the conduct attribute of members of the receptivity cohort, a recommendation is generated to add the candidate member to the receptivity cohort.

Claims

1. A processor-implemented method of generating a recommendation to add a member to a receptivity cohort, the processor-implemented method comprising:

defining a receptivity cohort, wherein each member of the receptivity cohort shares a conduct attribute, wherein the conduct attribute describes at least one of a facial expression, body language, and social interaction of a person, and wherein the conduct attribute has been predetermined to be an indicator of a level of receptiveness to a proposed future change in a set of circumstances;

a processor analyzing the conduct attribute and event metadata to generate a receptivity score for the receptivity cohort, wherein event metadata describes the proposed future change in the set of circumstances, and wherein the receptivity score indicates a level of receptiveness of members of the receptivity cohort to the proposed future change in the set of circumstances;

in response to determining that granular demographic information for members of the receptivity cohort is available, the processor processing the granular demographic information with the event metadata and conduct attribute to generate a weighted receptivity score for each member of the receptivity cohort, wherein the weighted receptivity score indicates a normalized level of receptivity of said each member to the proposed future change;

the processor retrieving biometric sensor data from a set of biometric sensors, wherein the biometric sensor data describe said at least one of the facial expression, body language and social interaction for a candidate member of the receptivity cohort;

the processor comparing the biometric sensor data for the candidate member to said conduct attribute of members of the receptivity cohort; and

the processor, in response to the biometric sensor data for the candidate member matching the conduct attribute of members of the receptivity cohort, generating a recommendation to add the candidate member to the receptivity cohort.

2. The processor-implemented method of claim 1, wherein the biometric sensor data from the set of biometric sensors is retrieved in response to receiving a notification of the proposed future change.

3. The processor-implemented method of claim 1, wherein the receptivity score comprises an upper threshold, and wherein members of the receptivity cohort are identified as receptive to the proposed future change in response to a determination that the receptivity score exceeds the upper threshold.

4. The processor-implemented method of claim 1, wherein the receptivity score comprises a lower threshold, and wherein members of the receptivity cohort are identified as receptive to the proposed future change in response to a determination that the receptivity score falls below the lower threshold.

5. The processor-implemented method of claim 1, wherein the conduct attribute is from a set of conduct attributes, and wherein the processor-implemented method further comprises:

assigning a value to each conduct attribute in the set of conduct attributes; and

aggregating the value of said each conduct attribute associated with each member of the receptivity cohort to generate a receptivity score, wherein the receptivity score is an aggregation of receptivity values for all members of the receptivity cohort.

6. The processor-implemented method of claim 1, wherein the conduct attribute is from a set of conduct attributes, and wherein the processor-implemented method further comprises:

comparing the set of conduct attributes with known patterns of expected conduct associated with a person that is receptive to the proposed future change to generate a receptivity score, wherein each known pattern is assigned a receptivity value, and wherein values for known patterns that match conduct attributes for the receptivity cohort are weighted and aggregated to generate the receptivity score.

7. The processor-implemented method of claim 1, wherein event metadata describes the proposed future change in the set of circumstances, and wherein the processor-implemented method further comprises:

responsive to determining description data for each member of the receptivity cohort is available, retrieving the description data for each member of the receptivity cohort, wherein the description data comprises at least one of identification information, past history information, and current status information for said each member of the receptivity cohort; and

analyzing the description data with the conduct attribute and the event metadata to generate a receptivity score for said each member of the receptivity cohort.

8. The processor-implemented method of claim 1, wherein the proposed future change in the set of circumstances is at least one of a proposed future change in work location requiring that a worker relocate or commute across a greater distance, a proposed offer to sell goods or services to a customer at a given price, an offer to purchase goods or services from a person, a proposed request that a person leave a particular location, and a request that a person stop performing a given action.

9. A computer program product for generating a recommendation to add a member to a receptivity cohort, the computer program product comprising:

a non-transitory computer readable storage medium;

first program instructions to define a receptivity cohort, wherein each member of the receptivity cohort shares a conduct attribute, wherein the conduct attribute is from a set of conduct attributes, wherein the conduct attribute describes at least one of a facial expression, body language, and social interaction of a person, and wherein the conduct attribute has been predetermined to be an indicator of a level of receptiveness to a proposed future change in a set of circumstances;

second program instructions to analyze the conduct attribute and event metadata to generate a receptivity score for the receptivity cohort, wherein event metadata describes the proposed future change in the set of circumstances, and wherein the receptivity score indicates a level of receptiveness of members of the receptivity cohort to the proposed future change in the set of circumstances;

third program instructions to, in response to determining that granular demographic information for members of the receptivity cohort is available, process the granular demographic information with the event metadata and conduct attribute to generate a weighted receptivity score for each member of the receptivity cohort, wherein the weighted receptivity score indicates a normalized level of receptivity of said each member to the proposed future change;

fourth program instructions to retrieve biometric sensor data from a set of biometric sensors, wherein the biometric sensor data describe said at least one of the facial expression, body language and social interaction for a candidate member of the receptivity cohort;

fifth program instructions to compare the biometric sensor data for the candidate member to said conduct attribute of members of the receptivity cohort; and

sixth program instructions to, in response to the biometric sensor data for the candidate member matching the conduct attribute of members of the receptivity cohort, generate a recommendation to add the candidate member to the receptivity cohort; and

wherein

the first, second, third, fourth, fifth, and sixth program instructions are stored on the non-transitory computer readable storage medium.

10. The computer program product of claim 9, wherein the biometric sensor data from the set of biometric sensors is retrieved in response to receiving a notification of the proposed future change.

11. The computer program product of claim 9, wherein the receptivity score comprises an upper threshold, and wherein members of the receptivity cohort are identified as receptive to the proposed future change in response to a determination that the receptivity score exceeds the upper threshold.

12. The computer program product of claim 9, wherein the receptivity score comprises a lower threshold, and wherein members of the receptivity cohort are identified as receptive to the proposed future change in response to a determination that the receptivity score falls below the lower threshold.

13. A computer system comprising:

a processor, a computer readable memory, and a computer readable storage media;

first program instructions to define a receptivity cohort, wherein each member of the receptivity cohort shares a conduct attribute, wherein the conduct attribute is from a set of conduct attributes, wherein the conduct attribute describes at least one of a facial expression, body language, and social interaction of a person, and wherein the conduct attribute has been predetermined to be an indicator of a level of receptiveness to a proposed future change in a set of circumstances;

second program instructions to analyze the conduct attribute and event metadata to generate a receptivity score for the receptivity cohort, wherein event metadata describes the proposed future change in the set of circumstances, and wherein the receptivity score indicates a level of receptiveness of members of the receptivity cohort to the proposed future change in the set of circumstances;

third program instructions to, in response to determining that granular demographic information for members of the receptivity cohort is available, process the granular demographic information with the event metadata and conduct attribute to generate a weighted receptivity score for each member of the receptivity cohort, wherein the weighted receptivity score indicates a normalized level of receptivity of said each member to the proposed future change;

fourth program instructions to retrieve biometric sensor data from a set of biometric sensors, wherein the biometric sensor data describe said at least one of the facial expression, body language and social interaction for a candidate member of the receptivity cohort;

fifth program instructions to compare the biometric sensor data for the candidate member to said conduct attribute of members of the receptivity cohort; and

sixth program instructions to, in response to the biometric sensor data for the candidate member matching the conduct attribute of members of the receptivity cohort, generate a recommendation to add the candidate member to the receptivity cohort; and

wherein

the first, second, third, fourth, fifth, and sixth program instructions are stored on the computer readable storage media for execution by the processor via the computer readable memory.

14. The computer system of claim 13, wherein the biometric sensor data from the set of biometric sensors is retrieved in response to receiving a notification of the proposed future change.

15. The computer system of claim 13, wherein event metadata describes the proposed future change in the set of circumstances, and wherein the computer system further comprises:

seventh program instructions to analyze the conduct attribute and event metadata to generate the receptivity score for the receptivity cohort, wherein the receptivity score indicates a level of receptiveness of members of the receptivity cohort to the proposed future change in the set of circumstances; and

wherein

the seventh program instructions are stored on the computer readable storage media for execution by the processor via the computer readable memory.

16. The computer system of claim 13, wherein the receptivity score comprises an upper threshold, and wherein members of the receptivity cohort are identified as receptive to the proposed future change in response to a determination that the receptivity score exceeds the upper threshold.

17. The computer system of claim 13, wherein the receptivity score comprises a lower threshold, and wherein members of the receptivity cohort are identified as receptive to the proposed future change in response to a determination that the receptivity score falls below the lower threshold.