ENTERPRISE ACTIVITY PATTERN ANALYSIS SYSTEM

• US 20140081959A1
• Filed: 03/15/2013
• Published: 03/20/2014
• Est. Priority Date: 09/17/2012
• Status: Active Grant

• Current Assignee: Accenture Global Services Limited (Accenture PLC)
• Original Assignee: Accenture Global Services Limited (Accenture PLC)
• Inventors: Kass, Alex, Shettigar, Sunil, Kim, Taemie, Thomas, Mary Catherine
• Granted Patent: US 9,275,161 B2
• Time in Patent Office: Days
• US Class Current: 707/723
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/986 Document structures and storage, e.g. HTML extensions
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: H04L 65/403 Arrangements for multi-party communication, e.g. for conferences data switching systems for conference H04L12/18; arrangements for connecting several subscribers to a common circuit, i.e. affording conference facilities H04M3/56; television conferencing systems H04N7/15
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

An enterprise activity pattern analysis system retrieves log data from a social networking system. The log data includes information characterizing user interactions with a team group space hosted by, or document uploaded to, the social networking system. The system analyzes the log data to detect patterns in the user interactions. The system embeds widgets into the group space and into the documents uploaded to the social networking system that provide visual representations of the pattern analysis.

Claims

1. An enterprise activity pattern analysis system, comprising:

a processor; and

a memory in communication with the processor, the memory comprising;

instructions that, when executed, cause the processor to;

retrieve log data from at least one social networking system, the log data comprising information characterizing user interactions with a team group space hosted by the social networking system;

analyze the log data to detect patterns in the user interactions;

embed a first interface component into the group space, wherein the first interface component comprises a visual representation of a first pattern analysis of the log data; and

embed a second interface component into a document uploaded to the group space, wherein the second interface component comprises a visual representation of a second pattern analysis of the log data.

2. The system of claim 1, wherein the first interface component comprises a dynamic listing of content objects associated with the group space ranked according to the frequency that users have contributed to the content.

3. The system of claim 1, wherein the first interface component comprises:

a dynamic listing of content objects associated with the group space ranked according the frequency that users have contributed to the content; and

a listing of users for each content object, wherein each listing of users is ranked according the amount of contribution to the respective content object.

4. The system of claim 1, wherein the second interface component comprises a listing of users that have contributed to the document.

5. The system of claim 4, wherein a document creator is listed first, followed by users that have edited the document, followed by users that have commented on the document.

6. The system of claim 1, wherein the second interface component comprises a graph embedded into the document in which an x-axis corresponds to time and a y-axis corresponds to a contribution score.

7. The system of claim 1, wherein the first interface component comprises a listing of recommended content based on the first pattern analysis.

8. A product, comprising:

a non-transitory computer-readable medium comprising instructions that, when executed, cause a computer processor to;

retrieve log data from at least one social networking system, the log data comprising information characterizing user interactions with a team group space hosted by the social networking system;

analyze the log data to detect patterns in the user interactions;

embed a first interface component into the group space, wherein the first interface component comprises a visual representation of a first pattern analysis of the log data; and

embed a second interface component into a document uploaded to the group space, wherein the second interface component comprises a visual representation of a second pattern analysis of the log data.

9. The system of claim 8, wherein the first interface component comprises a dynamic listing of content objects associated with the group space ranked according to the frequency that users have contributed to the content.

10. The system of claim 8, wherein the first interface component comprises:

a dynamic listing of content objects associated with the group space ranked according the frequency that users have contributed to the content; and

a listing of users for each content object, wherein each listing of users is ranked according the amount of contribution to the respective content object.

11. The system of claim 8, wherein the second interface component comprises a listing of users that have contributed to the document.

12. The system of claim 11, wherein a document creator is listed first, followed by users that have edited the document, followed by users that have commented on the document.

13. The system of claim 8, wherein the second interface component comprises a graph embedded into the document in which an x-axis corresponds to time and a y-axis corresponds to a contribution score.

14. The system of claim 8, wherein the first interface component comprises a listing of recommended content based on the first pattern analysis.

15. A method for analyzing enterprise activity patterns, comprising:

retrieving log data from at least one social networking system, the log data comprising information characterizing user interactions with a team group space hosted by the social networking system;

analyze, using a computer processor, the log data to detect patterns in the user interactions;

embedding a first interface component into the group space, wherein the first interface component comprises a visual representation of a first pattern analysis of the log data; and

embedding a second interface component into a document uploaded to the group space, wherein the second interface component comprises a visual representation of a second pattern analysis of the log data.

16. The method of claim 15, wherein embedding the first interface component comprises a generating a dynamic listing of content objects associated with the group space ranked according to the frequency that users have contributed to the content.

17. The method of claim 15, wherein embedding the first interface component comprises:

generating a dynamic listing of content objects associated with the group space ranked according the frequency that users have contributed to the content; and

generating a listing of users for each content object, wherein each listing of users is ranked according the amount of contribution to the respective content object.

18. The method of claim 15, wherein embedding the second interface component comprises providing a listing of users that have contributed to the document.

19. The method of claim 18, wherein a document creator is listed first, followed by users that have edited the document, followed by users that have commented on the document.

20. The method of claim 15, wherein embedding the second interface component comprises generating a graph embedded into the document in which an x-axis corresponds to time and a y-axis corresponds to a contribution score.

21. The method of claim 15, wherein embedding the first interface component comprises generating a listing of recommended content based on the first pattern analysis.