System and Method for the Automated Capture and Clustering of User Activities

• US 20090043646A1
• Filed: 08/06/2007
• Published: 02/12/2009
• Est. Priority Date: 08/06/2007
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Pingali, Gopal Sarma, Podlaseck, Mark E., Guven, Sinem
• Application Number:
  US11/834,443
• Publication Number:
  US 20090043646A1
• Time in Patent Office: Days
• US Class Current: 705/11
• CPC Class Codes: G06F 11/3409 for performance assessment
• CPC Class Codes: G06F 11/3466 Performance evaluation by tracing or monitoring
• CPC Class Codes: G06F 11/3476 Data logging G06F11/14, G06F11/2205 take precedence
• CPC Class Codes: G06F 2201/86 Event-based monitoring
• CPC Class Codes: G06Q 10/0633 Workflow analysis

Abstract

An electronic chronicling system and method that allows user actions performed by individuals, groups, or organizations to be automatically captured and grouped into chronicles based on activities, sub-activities and super-activities. The captured activities can then be filtered, viewed and navigated by a visualization and navigation mechanism to determine the relationships between activities and the time and resources spent on the various activities at fine levels of granularity and over various periods of time. The system allows users to gain greater insight into the relationship and resources spent on various activities in order to improve activity and process management efficiencies.

Claims

1. A data processing method, comprising:

capturing activities performed by at least one user;

clustering said captured activities based on shared commonality; and

filtering said captured activities by parameters of interest.

2. The data processing method according to claim 1, wherein said captured activities include one or more events occurring on at least one computer.

3. The data processing method according to claim 1, further comprising:

visualizing and navigating said captured activities in a chronicle bar and window at different levels of abstraction.

4. The data processing method according to claim 3, wherein said chronicle bar includes proximity parameters that further identify and define said captured activity.

5. The data processing method according to claim 4, wherein said proximity parameters include user or author, applications used, activity type, activity location, time, and artifacts involved.

6. The data processing method according to claim 3, wherein said window includes flexible menu options that selectively filter user events and control the functionality of activity capturing.

7. The data processing method according to claim 6, wherein said events include user activities, outgoing activities, incoming activities, shared activities, and group activities.

8. The data processing method according to claim 2, further comprising:

displaying a representation of a selected captured activity in a window.

9. The data processing method according to claim 8, further comprising:

launching the original application of said selected captured activity.

10. A data processing method, comprising:

providing one or more captured activities;

filtering said captured activities by parameters of interest;

navigating said captured activities in order to analyze user activities; and

utilizing said captured activities to improve activity management.

11. The data processing method according to claim 10, wherein said captured activities are performed by at least one user and clustered based on shared commonality.

12. The data processing method according to claim 10, further comprising:

visualizing and navigating said captured activities in a chronicle bar and window at different levels of abstraction.

13. The data processing method according to claim 12, wherein said chronicle bar includes proximity parameters.

14. The data processing method according to claim 13, wherein said proximity parameters include at least one of user or author, applications used, activity type, activity location, time, and artifacts involved.

15. The data processing method according to claim 12, wherein said window includes flexible menu options that selectively filter user events and control the functionality of activity capturing.

16. The data processing method according to claim 15, wherein said events include at least one of user activities, outgoing activities, incoming activities, shared activities, and group activities.

17. A visualization and navigation mechanism for browsing captured activities or events in a chronicle repository of a data processing system, comprising:

a first navigation bar in communication with a chronicle repository that flexibly focuses a search of events stored in said repository at a first varying degree of abstraction;

a second navigation bar in communication with said chronicle repository that flexibly focuses a search of events stored in said repository at a second varying degree of abstraction; and

a display window adjacent said first and second navigation bars that displays selected events, wherein the original application of said selected events are launched in said display window by right-clicking the selected event.

18. The visualization and navigation mechanism according to claim 17, further comprising:

at least one additional navigation bar in communication with said chronicle repository that flexibly focuses a search of events stored in said repository at an additional varying degree of abstraction.

19. The visualization and navigation mechanism according to claim 17, wherein said varying degrees of abstraction include at least one of user or author, applications used, activity type, activity location, time, and artifacts involved.

20. A computer program product comprising a computer useable medium including a computer readable program, wherein the computer readable program when executed on a computer causes the computer to:

capture activities performed by at least one user;

cluster said captured activities based on shared commonality;

filter said clustered activities by parameters of interest;

navigate said filtered activities to analyze said captured activities; and

utilize said captured activities to improve activity management.