Browse Prior Art Database

Autonomic Profiling of User Application Trends Disclosure Number: IPCOM000019253D
Original Publication Date: 2003-Sep-08
Included in the Prior Art Database: 2003-Sep-08
Document File: 3 page(s) / 58K

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Method to profile user trends, and autonomically schedule detected trends

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Autonomic Profiling of User Application Trends

       Currently computer users perform common groups of tasks throughout the usage cycle. Such tasks could include launching a specific application, launching particular websites, loading certain files, making backups, or anything a computer can be used for. However, the user must manually launch/load/configure each task. Tasks can be manually grouped into static script file(s) that perform the launching and loading of the tasks, e.g. dragging shortcuts into a Startup folder. These tasks must be also be maintained, for example if a particular website has keystroke requirements for navigation, the new keystrokes must be entered into the script files. This lends itself to an autonomic solution because most users are unaware that they use their computer in a certain pattern.

     The idea is to provide an application suite that profiles a user as they operate a computer and autonomically groups tasks based on usage. Criteria for grouping could be based on the user, time of day/week, network connections, OS system events, or any other heuristics pertaining to computer use that correlates to a task or group of tasks. Conversely, if a set of tasks are rarely leveraged, the tasks would be heuristically removed or modified.

     An agent/program would run that monitored computer use based on a set of dynamic criteria (See Autonomic User Profiling diagram below). When a pattern is detected, the agent/program could prompt the user to confirm an association which would be registered and then used when the correlating criteria is encountered again. A number of such groups could be made and managed manually as well as autonomically through a wizard like interface to the agent/program.


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Autonomic User Profiling

Agent loads

Agent monitors Event system

detected *

Gather event environment information **

Task Monitor

* Logged Events include

    - User login - Applications started/stoppe - Network changes
- Power state changes - Internet access (bookmark ** Criteria

- Time - Date - Network configuration - User
- Event name - Frequency - Threshold level - Pattern ID

Check agent scheduler

Inference Engine

Parse agent history for correlation patterns

 Pattern reaches threshold?


Update agent history

Register/deregister pattern with agent scheduler


 Confirm association

              Return to Return to monitor monitor

Update scheduler


Verify pattern criteria

Run pattern



Below is a description of the major blocks for the diagram above. T...