Process model generated using biased process mining

• US 9,355,371 B2
• Filed: 08/20/2013
• Issued: 05/31/2016
• Est. Priority Date: 03/15/2013
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Goodwin, Richard T., Mazzoleni, Pietro, Rembert, Aubrey J.
• Primary Examiner(s): Chaki, Kakali
• Assistant Examiner(s): Sitiriche, Luis
• Application Number:
  US13/970,826
• Publication Number:
  US 20140279769A1
• Time in Patent Office: 1,015 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: G06Q 10/067 Enterprise or organisation modelling
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes

Abstract

Embodiments relate to a method, system, and computer program product for a process model. The method includes extracting data associated with a process execution trace of a running process and extracting any prior knowledge data relating to the running process. The method also includes calculating at least one transition confidence parameter for the prior knowledge data; and identifying any existing process models relating to the running process. A confidence trace bias is also generated for any existing process model identified. An enhanced bias value is then calculated by combining the confidence trace bias value and value of the transition confidence parameter. Using as input the extracted process execution trace data, the prior knowledge data, the identified existing model and the enhanced bias value, a learned process model is then generated.

Claims

1. A computer program product for generating a process model, the computer program product comprising a non-transitory computer readable storage medium having computer readable program code embodied therewith, said computer readable program code being executable by a computer to:

extract data associated with a process execution trace of a running process and extract any prior knowledge data relating to said running process;

calculate at least one transition confidence parameter for said prior knowledge data;

identify any existing process models relating to said running process;

generate a confidence trace bias for any said existing process model identified;

calculate an enhanced bias value by combining said confidence trace bias value and value of said transition confidence parameter; and

generate a learned process model by using as input said extracted process execution trace data, said prior knowledge data, said identified existing model and said enhanced bias value.

2. The computer program product of claim 1, wherein said computer readable program code is executable by a computer to use said learned process model to automate said running process.

3. The computer program product of claim 2, wherein said computer readable program code is executable by a computer to extract said prior knowledge data with an associated transition confidence parameter.

4. The computer program product of claim 3, wherein said computer readable program code is executable by a computer to identify any matches in activities between any identified existing process models and said process execution trace.

5. The computer program product of claim 3, wherein said computer readable program code is executable by a computer to generate said confidence trace bias based on an identified match existing between said existing process model and said process execution trace.

6. The computer program product of claim 5, wherein said computer readable program code is executable by a computer to generate said confidence trace bias also based on said transition confidence parameter associated with said prior knowledge data.

7. The computer program product of claim 6, wherein said computer readable program code is executable by a computer to apply any existing model against bias enhanced trace to enhance or produce a new model.

8. The computer program product of claim 1, wherein said prior knowledge data includes data extracted from documentation and diagrams.

9. The computer program product of claim 1, wherein said computer readable program code is executable by a computer update said learned process model automatically when any of said input is revised.

10. The computer program product of claim 9, wherein said input includes matching of activities from a previous process model to one or more events.

11. A system comprising:

a processor for extracting process execution trace data and prior knowledge data relating to a running process from a memory;

said processor calculating a transition confidence parameter for said prior knowledge data;

a data manager in communication with said processor for identifying any existing process models relating to said running process;

said processor generating a confidence trace bias for any said existing process model identified and calculating an enhanced bias value by combining value of said confidence trace bias with said transition confidence parameter; and

said processor generating a learned process model by using as input said execution trace data, said prior knowledge data, said identified existing model and said enhanced bias value.

12. The system of claim 11, wherein said data manager is in processing communication with a network of computers.

13. The system of claim 11, wherein said processor uses said learned process model to automate said running process.

14. The system of claim 11, wherein said processor updates said learned process model automatically when any of said input is revised.

15. The system of claim 14, wherein said processor identifies any matches in activities between any identified existing process models and said process execution trace.

16. The system of claim 14, wherein said processor generates said confidence trace bias based on an identified match existing between said existing process model and said process execution trace.

17. The system of claim 16, wherein said processor generates said confidence trace bias also based on said transition confidence parameter associated with said prior knowledge data.

18. The system of claim 17, wherein said processor applies any existing model against bias enhanced trace to enhance or produce a new model.

19. The system of claim 11, wherein said process execution trace data includes database logs, server logs, and application logs.

20. The system of claim 11, wherein said process execution trace data includes event traces associated with one or more activities.