ENGAGEMENT SUMMARY GENERATION

• US 20150363489A1
• Filed: 06/12/2014
• Published: 12/17/2015
• Est. Priority Date: 06/12/2014
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Burton, Peter H., Byron, Donna K., Gupta, Manvendra
• Granted Patent: US 9,703,862 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/35 Clustering; Classification
• CPC Class Codes: G06Q 10/063118 Staff planning in a project environment
• CPC Class Codes: G06Q 10/06398 Performance of employee with respect to a job function
• CPC Class Codes: G06Q 10/1091 Recording time for administrative or management purposes

Abstract

A method and system for generating summary details is provided. The method includes retrieving event data of associated with a user. Attributes are extracted from the event data and the event data is segmented into logical groups of related activities performed by the user. Key information and associated attributes of each logical group are identified and in response the user is evaluated. The logical groups of related activities are ranked and presented to the user. In response, an engagement summary associated with the user and the logical groups is generated.

Claims

1. A method comprising:

retrieving, by a computer processor of a computing system, event data comprising time stamped artifacts generated during activities performed by a user;

extracting, by said computer processor from said event data, attributes associated with said activities performed by said user;

segmenting, by said computer processor based on said attributes, said event data into logical groups of related activities associated with said activities performed by said user;

identifying, by said computer processor, key information associated with each logical group of said logical groups of related activities with respect to said activities performed by said user;

identifying, by said computer processor from said key information, logical group attributes associated with each said logical group;

evaluating, by said computer processor executing a sentiment analysis with respect to said event data and communications of said user, said user;

ranking, by said computer processor based on results of said evaluating, said logical groups of related activities;

presenting, by said computer processor to said user said logical groups of related activities according to results of said ranking; and

generating, by said computer processor based on said ranking, an engagement summary associated with said user and said logical groups of related activities.

2. The method of claim 1, wherein said time stamped artifacts comprise artifacts selected from the group consisting of emails, personal information managers (PIMS), personal activity logs and associated attachments.

3. The method of claim 1, wherein said extracting said attributes comprises performing a dedicated information extraction process for an associated format using a selected library for extracting targeted information from common areas of said event data.

4. The method of claim 3, wherein said targeted information is selected from the group consisting of customer satisfaction information, logical group risk and challenge information, and logical personnel information.

5. The method of claim 1, further comprising:

organizing, by said computer processor executing a temporal analysis algorithm, said activities.

6. The method of claim 1, wherein said identifying said key information comprises:

locating user attributes describing user participation and contribution associated with said user; and

identifying roles/IDs of participants of said logical groups of related activities.

7. The method of claim 1, wherein said evaluating said user comprises:

locating recognition points within documents associated with respective logical group/episode clusters.

8. The method of claim 1, wherein said ranking comprises:

performing a ranking process with respect to said logical groups of related activities in terms of relevance in response to a specified prompt from an application being completed, wherein said specified prompt is a selected from the group consisting of a request to describe a logical group with a high customer satisfaction, a request to describe a leader role, and a request to describe a work function using a specified scripting language; and

matching user activities of said user with information specified in a template via executing similarity judgment algorithms.

9. The method of claim 8, wherein similarity judgment algorithms comprise algorithms selected from the group consisting of an evidence of topical matching algorithm using semantic and entity analytics against an agenda/description of a specified event, an information algorithm associated with attendees of said specified retrieved from personal profiles of social media repositories associated with said user, and an attachment algorithm associated with attachments including a presentation slide deck attached to a calendar entry associated with the specified event or multi-media files associated with said specified event.

10. The method of claim 1, further comprising:

providing at least one support service for at least one of creating, integrating, hosting, maintaining, and deploying computer-readable code in the computing system, said code being executed by the computer processor to implement;

said retrieving, said extracting, said segmenting, said identifying said key information, said identifying said logical group attributes, said evaluating, said ranking, said presenting, and said generating.

11. A computing system comprising a computer processor coupled to a computer-readable memory unit, said memory unit comprising instructions that when executed by the computer processor implements a method comprising:

retrieving, by said computer processor, event data comprising time stamped artifacts generated during activities performed by a user;

extracting, by said computer processor from said event data, attributes associated with said activities performed by said user;

segmenting, by said computer processor based on said attributes, said event data into logical groups of related activities associated with said activities performed by said user;

identifying, by said computer processor, key information associated with each logical group of said logical groups of related activities with respect to said activities performed by said user;

identifying, by said computer processor from said key information, logical group attributes associated with each said logical group;

evaluating, by said computer processor executing a sentiment analysis with respect to said event data and communications of said user, said user;

ranking, by said computer processor based on results of said evaluating, said logical groups of related activities;

presenting, by said computer processor to said user said logical groups of related activities according to results of said ranking; and

generating, by said computer processor based on said ranking, an engagement summary associated with said user and said logical groups of related activities.

12. The computing system of claim 11, wherein said time stamped artifacts comprise artifacts selected from the group consisting of emails, personal information managers (PIMS), personal activity logs and associated attachments.

13. The computing system of claim 11, wherein said extracting said attributes comprises performing a dedicated information extraction process for an associated format using a selected library for extracting targeted information from common areas of said event data.

14. The computing system of claim 13, wherein said targeted information is selected from the group consisting of customer satisfaction information, logical group risk and challenge information, and logical personnel information.

15. The computing system of claim 11, wherein said method further comprises:

organizing, by said computer processor executing a temporal analysis algorithm, said activities.

16. The computing system of claim 11, wherein said identifying said key information comprises:

locating user attributes describing user participation and contribution associated with said user; and

identifying roles/IDs of participants of said logical groups of related activities.

17. The computing system of claim 11, wherein said evaluating said user comprises:

locating recognition points within documents associated with respective logical group/episode clusters.

18. The computing system of claim 11, wherein said ranking comprises:

performing a ranking process with respect to said logical groups of related activities in terms of relevance in response to a specified prompt from an application being completed, wherein said specified prompt is a selected from the group consisting of a request to describe a logical group with a high customer satisfaction, a request to describe a leader role, and a request to describe a work function using a specified scripting language; and

matching user activities of said user with information specified in a template via executing similarity judgment algorithms.

19. The computing system of claim 18, wherein similarity judgment algorithms comprise algorithms selected from the group consisting of an evidence of topical matching algorithm using semantic and entity analytics against an agenda/description of a specified event, an information algorithm associated with attendees of said specified retrieved from personal profiles of social media repositories associated with said user, and an attachment algorithm associated with attachments including a presentation slide deck attached to a calendar entry associated with the specified event or multi-media files associated with said specified event.

20. A computer program product, comprising a computer readable hardware storage device storing a computer readable program code, said computer readable program code comprising an algorithm that when executed by a computer processor of a computing system implements a method, said method comprising:

retrieving, by said computer processor, event data comprising time stamped artifacts generated during activities performed by a user;

extracting, by said computer processor from said event data, attributes associated with said activities performed by said user;

segmenting, by said computer processor based on said attributes, said event data into logical groups of related activities associated with said activities performed by said user;

identifying, by said computer processor, key information associated with each logical group of said logical groups of related activities with respect to said activities performed by said user;

identifying, by said computer processor from said key information, logical group attributes associated with each said logical group;

evaluating, by said computer processor executing a sentiment analysis with respect to said event data and communications of said user, said user;

ranking, by said computer processor based on results of said evaluating, said logical groups of related activities;

presenting, by said computer processor to said user said logical groups of related activities according to results of said ranking; and

generating, by said computer processor based on said ranking, an engagement summary associated with said user and said logical groups of related activities.