CONVERSION OF A PROCEDURAL PROCESS MODEL TO A HYBRID PROCESS MODEL

• US 20180203426A1
• Filed: 02/19/2018
• Published: 07/19/2018
• Est. Priority Date: 09/23/2015
• Status: Active Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Li, Bing, Li, Xiang, Lian, Xiao Jian, Liu, Dan, Liu, Haifeng, Mei, Jing, Xie, Guo Tong, Yu, Yi Qin, Zhang, Jing
• Application Number:
  US15/898,983
• Publication Number:
  US 20180203426A1
• Time in Patent Office: Days
• CPC Class Codes: G05B 17/02 electric

Abstract

Disclosed are a computer-implemented method for converting a procedural process model for a process to a hybrid process model, a system and a computer program product. In this method, a plurality of steps of the process which are included in the procedural process model may be clustered selectively according to historical execution information of the plurality of steps, to generate a plurality of candidate cluster set. One candidate cluster set satisfying a first condition may be selected from the plurality of candidate cluster sets. Then, the procedural process model may be converted into the hybrid process model according to the selected candidate cluster set.

Claims

1. A computer-implemented method for converting a procedural process model for a process to a hybrid process model, comprising:

selectively clustering a plurality of steps of the process which are included in the procedural process model, according to a historical execution information of the plurality of steps, to generate a plurality of candidate cluster sets;

selecting one candidate cluster set satisfying a first condition from the plurality of candidate cluster sets; and

converting the procedural process model into the hybrid process model according to the selected candidate cluster set.

2. The computer-implemented method of claim 1, further comprising:

determining the historical execution information of the plurality of steps according to a plurality of history logs associated with a historical execution of the process.

3. The computer-implemented method of claim 2, wherein the historical execution information of the plurality of steps includes at least one of ratios of history logs in which connections between the plurality of steps occur to the plurality of history logs, ratios of history logs in which common data items for the respective steps occur to the plurality of history logs, and ratios of history logs in which common roles for the respective steps occur to the plurality of history logs.

4. The computer-implemented method of claim 1, wherein the selectively clustering a plurality of steps of the process which are included in the procedural process model, according to historical execution information of the plurality of steps, to generate a plurality of candidate cluster set comprises:

determining correlation degrees between a plurality of clusters which the plurality of steps act as respectively; and

clustering clusters whose correlation degree satisfies a second condition, to generate a first candidate cluster set including a plurality of clusters.

5. The computer-implemented method of claim 4, wherein the selectively clustering a plurality of steps of the process which are included in the procedural process model, according to the historical execution information of the plurality of steps, to generate a plurality of candidate cluster set further comprises:

determining correlation degrees between the respective clusters in the first candidate cluster set; and

clustering clusters whose correlation degree satisfies a third condition, to generate a second candidate cluster set including a plurality of clusters.

6. The computer-implemented method of claim 1, wherein the selecting one candidate cluster set satisfying a first condition from the plurality of candidate cluster sets comprises:

calculating clustering qualities of the plurality of candidate cluster sets; and

selecting one candidate cluster set based on the clustering qualities, as the candidate cluster set satisfying the first condition, from the plurality of candidate cluster sets.

7. The computer-implemented method of claim 6, wherein a clustering quality of a candidate cluster set increases in response to that correlation degrees between respective clusters in the candidate cluster set decrease, or in response to that correlation degrees between steps included in each cluster in the candidate cluster set increase.

8. The computer-implemented method of claim 1, wherein the converting the procedural process model into the hybrid process model according to the selected one candidate cluster set comprises:

converting the procedural process model into the hybrid process model by converting respective clusters in the selected one candidate cluster set into corresponding tasks and converting connections between the respective clusters into constraints for corresponding tasks.