Determining group attributes and matching tasks to a group

• US 10,346,772 B2
• Filed: 06/10/2014
• Issued: 07/09/2019
• Est. Priority Date: 06/10/2014
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Mahmud, Jalal U., Pal, Aditya, Wang, Fei
• Primary Examiner(s): Padot, Timothy
• Assistant Examiner(s): Walker, III, George H
• Application Number:
  US14/300,342
• Publication Number:
  US 20150356480A1
• Time in Patent Office: 1,855 Days
• Field of Search: 705 713
• CPC Class Codes: G06Q 10/06311 Scheduling, planning or task assignment for a person or group
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

In a method for determining group attributes and matching tasks to a group, a plurality of individual attributes for members of a first group of a plurality of groups are determined, wherein each individual attribute has a type. Parameters of a first distribution of at least one type of individual attribute across members of the first group are estimated. Group attributes of the first group are determined based, at least in part, on the estimated parameters of the first distribution of at least one type of individual attribute. The determined group attributes of the first group are stored in a repository, wherein the repository includes group attributes associated with each group of the plurality of groups. A task is received, wherein the task is associated with a specific group attribute and the task is matched to one group of the plurality of groups based on the specific group attribute.

Claims

1. A method for determining group attributes and matching tasks to a group, the method comprising:

receiving, by one or more processors of server computer hosting a social networking platform, information from a plurality of client computers, wherein each client computer of the plurality of client computers corresponds to a respective member of the social networking platform, and wherein the received information includes;

(i) membership information of the social networking platform corresponding to each member, and (ii) activity information corresponding to each member'"'"'s use of the social networking platform;

determining, by one or more processors of the server computer, a plurality of individual attributes for members of a first group of a plurality of groups of the social networking platform, wherein each individual attribute of the plurality of individual attributes has a type, and wherein the individual attributes of the plurality of individual attributes are determined, at least in part, from the received membership information and activity information;

estimating, by one or more processors of the server computer, one or more parameters of a first distribution of at least one type of individual attribute across members of the first group, wherein the first distribution is determined by;

(i) a multivariate normal distribution, (ii) a maximum-likelihood estimation (MLE), and (iii) a parametric distribution model;

determining, by one or more processors of the server computer, one or more group attributes of the first group based, at least in part, on the one or more estimated parameters of the first distribution of at least one type of individual attribute;

storing, by one or more processors of the server computer, the one or more determined group attributes of the first group in a repository, wherein the repository includes group attributes associated with each group of the plurality of groups, including the first group;

receiving, by one or more processors of the server computer, a task, wherein the task is associated with a specific group attribute;

matching, by one or more processors of the server computer, the task to one group of the plurality of groups based on the specific group attribute and a cluster analysis; and

sending, by one or more processors of the server computer, the task to the respective client computers of the respective members of the matched group.

2. The method of claim 1, further comprising:

determining, by one or more processors of the server computer, a plurality of individual attributes for members of a second group of the plurality of groups, wherein each individual attribute has a type, and wherein the individual attributes of the plurality of individual attributes for members of the second group are determined, at least in part, from the received membership information and activity information;

determining, by one or more processors of the server computer, that the second group has a number of members exceeding a pre-defined threshold;

determining, by one or more processors of the server computer, at least two subgroups of the second group;

estimating, by one or more processors of the server computer, one or more parameters of a second distribution of at least one type of individual attribute across members of the second group;

determining, by one or more processors of the server computer, one or more group attributes of each subgroup of the plurality of subgroups based, at least in part, on the one or more estimated parameters of the second distribution; and

determining, by one or more processors of the server computer, group attributes of the second group based, at least in part, on the one or more determined group attributes of each subgroup of the plurality of subgroups.

3. The method of claim 2, further comprising:

storing, by one or more processors of the server computer, the one or more determined group attributes of the second group in a repository on the server computer, wherein the repository includes group attributes associated with each group of the plurality of groups including the first group and the second group;

receiving, by one or more processors of the server computer, a second task, wherein the second task is associated with a second specific group attribute; and

matching, by one or more processors of the server computer, the second task to one group of the plurality of groups based, at least in part, on the second specific group attribute.

4. The method of claim 1, wherein the plurality of members of the first group includes fewer than all members of the first group.

5. The method of claim 2, wherein the plurality of subgroups of the second group each include members that have an individual attribute of a certain type.

6. The method of claim 1, wherein the plurality of members of the first group includes all members of the first group.

7. The method of claim 1, wherein estimating one or more parameters of the first determined distribution comprises estimating one or more parameters of the first determined distribution using a maximum-likelihood estimation method.

8. A computer program product for determining group attributes and matching tasks to a group, 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 information from a plurality of client computers, wherein each client computer of the plurality of client computers corresponds to a respective member of a social networking platform, and wherein the received information includes;

(i) membership information of the social networking platform corresponding to each member, and (ii) activity information corresponding to each member'"'"'s use of the social networking platform;

program instructions to determine a plurality of individual attributes for members of a first group of a plurality of groups of the social networking platform, wherein each individual attribute of the plurality of individual attributes has a type, and wherein the individual attributes of the plurality of individual attributes are determined, at least in part, from the received membership information and activity information;

program instructions to estimate one or more parameters of a first distribution of at least one type of individual attribute across members of the first group, wherein the first distribution is determined by;

(i) a multivariate normal distribution, (ii) a maximum-likelihood estimation (MLE), and (iii) a parametric distribution model;

program instructions to determine one or more group attributes of the first group based, at least in part, on the one or more estimated parameters of the first distribution of at least one type of individual attribute;

program instructions to store the one or more determined group attributes of the first group in a repository, wherein the repository includes group attributes associated with each group of the plurality of groups, including the first group;

program instructions to receive a task, wherein the task is associated with a specific group attribute;

program instructions to match the task to one group of the plurality of groups based on the specific group attribute and a cluster analysis; and

program instructions to send the task to the respective client computers of the respective members of the matched group.

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

determine a plurality of individual attributes for members of a second group of the plurality of groups, wherein each individual attribute has a type, and wherein the individual attributes of the plurality of individual attributes for members of the second group are determined, at least in part, from the received membership information and activity information;

determine that the second group has a number of members exceeding a pre-defined threshold;

determine at least two subgroups of the second group;

estimate one or more parameters of a second distribution of at least one type of individual attribute across members of the second group;

determine one or more group attributes of each subgroup of the plurality of subgroups based, at least in part, on the one or more estimated parameters of the second distribution; and

determine group attributes of the second group based, at least in part, on the one or more determined group attributes of each subgroup of the plurality of subgroups.

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

store the one or more determined group attributes of the second group in a repository on a server computer, wherein the repository includes group attributes associated with each group of the plurality of groups including the first group and the second group;

receive a second task, wherein the second task is associated with a second specific group attribute; and

match the second task to one group of the plurality of groups based, at least in part, on the second specific group attribute.

11. The computer program product of claim 8, wherein the plurality of members of the first group includes fewer than all members of the first group.

12. The computer program product of claim 9, wherein the plurality of subgroups of the second group each include members that have an individual attribute of a certain type.

13. The computer program product of claim 8, wherein the plurality of members of the first group includes all members of the first group.

14. The computer program product of claim 8, wherein estimating one or more parameters of the first determined distribution comprises estimating one or more parameters of the first determined distribution using a maximum-likelihood estimation method.

15. A computer system for determining group attributes and matching tasks to a group, 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 information from a plurality of client computers, wherein each client computer of the plurality of client computers corresponds to a respective member of a social networking platform, and wherein the received information includes;

(i) membership information of the social networking platform corresponding to each member, and (ii) activity information corresponding to each member'"'"'s use of the social networking platform;

program instructions to determine a plurality of individual attributes for members of a first group of a plurality of groups of the social networking platform, wherein each individual attribute of the plurality of individual attributes has a type, and wherein the individual attributes of the plurality of individual attributes are determined, at least in part, from the received membership information and activity information;

program instructions to estimate one or more parameters of a first distribution of at least one type of individual attribute across members of the first group, wherein the first distribution is determined by;

(i) a multivariate normal distribution, (ii) a maximum-likelihood estimation (MLE), and (iii) a parametric distribution model;

program instructions to determine one or more group attributes of the first group based, at least in part, on the one or more estimated parameters of the first distribution of at least one type of individual attribute;

program instructions to store the one or more determined group attributes of the first group in a repository, wherein the repository includes group attributes associated with each group of the plurality of groups, including the first group;

program instructions to receive a task, wherein the task is associated with a specific group attribute;

program instructions to match the task to one group of the plurality of groups based on the specific group attribute and a cluster analysis; and

program instructions to send the task to the respective client computers of the respective members of the matched group.

16. The computer system of claim 15, further comprising program instructions, stored on the one or more computer readable storage media for execution by at least one of the one or more processors, to:

determine a plurality of individual attributes for members of a second group of the plurality of groups, wherein each individual attribute has a type, and wherein the individual attributes of the plurality of individual attributes for members of the second group are determined, at least in part, from the received membership information and activity information;

determine that the second group has a number of members exceeding a pre-defined threshold;

determine at least two subgroups of the second group;

estimate one or more parameters of a second distribution of at least one type of individual attribute across members of the second group;

determine one or more group attributes of each subgroup of the plurality of subgroups based, at least in part, on the one or more estimated parameters of the second distribution; and

determine group attributes of the second group based, at least in part, on the one or more determined group attributes of each subgroup of the plurality of subgroups.

17. The computer system of claim 16, further comprising program instructions, stored on the one or more computer readable storage media for execution by at least one of the one or more processors, to:

store the one or more determined group attributes of the second group in a repository on a server computer, wherein the repository includes group attributes associated with each group of the plurality of groups including the first group and the second group;

receive a second task, wherein the second task is associated with a second specific group attribute; and

match the second task to one group of the plurality of groups based, at least in part, on the second specific group attribute.

18. The computer system of claim 15, wherein the plurality of members of the first group includes all members of the first group.

19. The computer system of claim 15, wherein the plurality of members of the first group includes fewer than all members of the first group.

20. The computer system of claim 15, wherein estimating one or more parameters of the first determined distribution comprises estimating one or more parameters of the first determined distribution using a maximum-likelihood estimation method.