System and method for managing and identifying subject matter experts

• US 9,317,574 B1
• Filed: 10/07/2013
• Issued: 04/19/2016
• Est. Priority Date: 06/11/2012
• Status: Expired due to Fees

• Current Assignee: Quest Software, Inc.
• Original Assignee: Dell Software, Inc. (Dell Technologies Inc.)
• Inventors: Brisebois, Michel, Johnstone, Curtis
• Primary Examiner(s): Chen, Alan
• Application Number:
  US14/047,162
• Time in Patent Office: 925 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: G06F 16/254 Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
• CPC Class Codes: G06F 16/258 Data format conversion from or to a database
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 21/62 Protecting access to data via a platform, e.g. using keys or access control rules
• CPC Class Codes: G06F 21/6218 to a system of files or objects, e.g. local or distributed file system or database
• CPC Class Codes: G06F 21/6227 where protection concerns the structure of data, e.g. records, types, queries
• CPC Class Codes: G06F 2216/01 Automatic library building
• CPC Class Codes: G06F 2216/03 Data mining
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

In one embodiment, a method includes collecting communications from a plurality of sources. The method further includes selecting a set of topics and a set of users. In addition, the method includes, for each user, identifying, from the collected communications, conversations in which the user has participated. Moreover, the method includes, for each topic, for each user: measuring a proportion of the identified conversations that contain content suggestive of the topic; analyzing timing of the identified conversations; and examining relationships among data attributes of the identified conversations. Further, the method includes generating multidimensional expertise data. The multidimensional expertise data is representative of the user'"'"'s expertise on the topic. The multidimensional expertise data includes a topical dimension, an expertise-scope dimension, and a timeline dimension. The method also includes, for each topic, ranking the set of users by expertise index. Also, the method includes providing a searchable interface.

Claims

1. A method comprising:

on a computer system comprising at least one processor and memory, collecting communications from a plurality of sources;

the computer system selecting a set of topics and a set of users;

for each user, the computer system identifying, from the collected communications, conversations in which the user has participated;

for each said topic, for each said user;

the computer system measuring a proportion of the identified conversations that contain content suggestive of the topic, the measuring yielding at least one topical metric;

the computer system analyzing timing of the identified conversations, the analyzing yielding at least one timing metric;

the computer system examining relationships among data attributes of the identified conversations, the examining yielding at least one expertise-scope metric;

the computer system generating multidimensional expertise data from the at least one topical metric, the at least one timing metric, and the at least one expertise-scope metric, wherein the multidimensional expertise data is representative of the user'"'"'s expertise on the topic, wherein the multidimensional expertise data comprises a topical dimension, an expertise-scope dimension, and a timeline dimension;

wherein the multidimensional expertise data comprises an expertise index for the user; and

for each said topic, the computer system ranking the set of users by the expertise index; and

the computer system providing a searchable interface, wherein the multidimensional expertise data is searchable by one or more topical parameters mapped to the topical dimension, by one or more scope parameters mapped to the expertise-scope dimension, and by one or more timeline parameters mapped to the timeline dimension.

2. The method of claim 1, wherein the generating comprises:

assessing the user'"'"'s expertise on the topic based, at least in part, on the at least one topical metric, wherein the assessing comprises determining the expertise index;

discovering a scope of the user'"'"'s expertise based, at least in part, on the at least one expertise-scope metric; and

ascertaining a timeline of the user'"'"'s expertise based, at least in part, on the at least one timing metric.

3. The method of claim 2, comprising, for each said topic, for each said user, storing the multidimensional expertise data, wherein the storing comprises:

storing the expertise index as part of the topical dimension;

storing the scope as part of the expertise-scope dimension; and

storing the timeline as part of the timeline dimension.

4. The method of claim 3, wherein the measuring comprises:

applying, via an a priori classification engine, at least one taxonomy to the collected communications; and

wherein the at least one taxonomy comprises one or more words associated with the topic.

5. The method of claim 4, wherein the at least one taxonomy comprises a taxonomy selected from the group consisting of:

a taxonomy resulting from ingestion of an organization'"'"'s content, a human-resources taxonomy for the organization, and a directory-service taxonomy.

6. The method of claim 4, wherein the applying comprises enumerating conversations containing the one or more words, the enumerating yielding the at least one topical metric.

7. The method of claim 3, wherein:

the analyzing of timing and the examining of relationships are performed via an a posteriori classification engine; and

the a posteriori classification engine produces the at least one expertise-scope metric and the at least one timing metric.

8. The method of claim 2, wherein the discovering of the scope comprises assigning at least one scope classification to the user, wherein the at least one scope classification is selected from the group consisting of:

evangelist, knowledge manager, knowledge creator, and influencee.

9. The method of claim 2, wherein the ascertaining comprises assigning at least one timeline classification to the user, wherein the at least one timeline classification is selected from the group consisting of:

long-time expert, deep-domain expert, cutting-edge expert, and strategic expert.

10. The method of claim 2, comprising managing a subject matter expert (SME) search, the managing comprising:

receiving a SME request from a requestor, wherein the SME request comprises at least one topical parameter selected from the one or more topical parameters, at least one scope parameter selected from the one or more scope parameters, and at least one timeline parameter selected from the one or more timeline parameters;

wherein the at least one topical parameter specifies at least one topic of the set of topics;

searching the expertise data via the at least one topical parameter, the at least one scope parameter, and the at least one timeline parameter; and

identifying one or more SMEs responsive to the SME request.

11. The method of claim 10, wherein:

the at least one topical parameter specifies a desired expertise level; and

the desired expertise level is associated with at least one of;

a value of the expertise index; and

a range of values of the expertise index.

12. The method of claim 10, wherein the managing comprises facilitating a negotiation process between the requestor and the one or more SMEs, the facilitating comprising:

allowing the requestor to request a SME service from at least one SME of the one or more SMEs; and

allowing the at least one SME to accept the request.

13. The method of claim 12, comprising, responsive to the at least one SME accepting the request, providing gamification credit to the at least one SME.

14. The method of claim 10, comprising monitoring participation of each user of the set of users relative to SME requests.

15. The method of claim 14, wherein the generating comprises classifying each said user into one or more of a plurality of participation levels based, at least in part, on the user'"'"'s historical participation relative to SME requests.

16. The method of claim 15, wherein:

the multidimensional expertise data is searchable by one or more participation parameters mapped to the plurality of participation levels;

the SME request comprises at least one participation parameter selected from the one or more participation parameters; and

the searching comprises searching the multidimensional expertise data via the at least one participation parameter.

17. The method of claim 10, wherein the returning comprises identifying the one or more SMEs to the requestor responsive to a determination that the requestor has sufficient access rights.

18. The method of claim 10, wherein:

the SME request dynamically establishes a distribution list, the distribution list comprising the one or more SMEs; and

the SME request dynamically updates the distribution list each time the SME request is executed.

19. The method of claim 1, comprising:

identifying at least two users in the set of users that refer to a same individual; and

merging the at least two users.

20. The method of claim 1, wherein the searchable interface allows an authorized user to manually change at least a portion of the multidimensional expertise data.

21. An information handling system comprising:

a processing unit, wherein the at least one processing unit is operable to implement a method comprising;

collecting communications from a plurality of sources;

selecting a set of topics and a set of users;

for each user, identifying, from the collected communications, conversations in which the user has participated;

for each said topic, for each said user;

measuring a proportion of the identified conversations that contain content suggestive of the topic, the measuring yielding at least one topical metric;

analyzing timing of the identified conversations, the analyzing yielding at least one timing metric;

examining relationships among data attributes of the identified conversations, the examining yielding at least one expertise-scope metric;

generating multidimensional expertise data from the at least one topical metric, the at least one timing metric, and the at least one expertise-scope metric, wherein the multidimensional expertise data is representative of the user'"'"'s expertise on the topic, wherein the multidimensional expertise data comprises a topical dimension, an expertise-scope dimension, and a timeline dimension;

wherein the multidimensional expertise data comprises an expertise index for the user; and

for each said topic, ranking the set of users by the expertise index; and

providing a searchable interface, wherein the multidimensional expertise data is searchable by one or more topical parameters mapped to the topical dimension, by one or more scope parameters mapped to the expertise-scope dimension, and by one or more timeline parameters mapped to the timeline dimension.

22. A computer-program product comprising a non-transitory computer-usable medium having computer-readable program code embodied therein, the computer-readable program code adapted to be executed to implement a method comprising:

collecting communications from a plurality of sources;

selecting a set of topics and a set of users;

for each user, identifying, from the collected communications, conversations in which the user has participated;

for each said topic, for each said user;

measuring a proportion of the identified conversations that contain content suggestive of the topic, the measuring yielding at least one topical metric;

analyzing timing of the identified conversations, the analyzing yielding at least one timing metric;

examining relationships among data attributes of the identified conversations, the examining yielding at least one expertise-scope metric;

generating multidimensional expertise data from the at least one topical metric, the at least one timing metric, and the at least one expertise-scope metric, wherein the multidimensional expertise data is representative of the user'"'"'s expertise on the topic, wherein the multidimensional expertise data comprises a topical dimension, an expertise-scope dimension, and a timeline dimension;

wherein the multidimensional expertise data comprises an expertise index for the user; and

for each said topic, ranking the set of users by the expertise index; and

providing a searchable interface, wherein the multidimensional expertise data is searchable by one or more topical parameters mapped to the topical dimension, by one or more scope parameters mapped to the expertise-scope dimension, and by one or more timeline parameters mapped to the timeline dimension.