Behavior pattern mining method based on pairing of business process logs and entity tracks

Abstract

The invention discloses a behavior pattern mining method based on pairing of business process logs and entity tracks. The behavior pattern mining method includes the steps that event log datasets are converted into entity track datasets, the entity track datasets are subjected to layered clustering with a synthesis clustering algorithm, an entity track ID guide tree is obtained, and a paired matrix containing all the entity track datasets is obtained with the guide tree as an index; the paired matrix is subjected to traversal to gather elements with same activity name attributes to obtain activity blocks, frequent activity blocks and frequent combinations are selected according to the sum of the numbers of combined-appearing times of the activity name attributes and the activity executor attributes in the activity blocks, the number of appearing times of the activity name attributes and the number of appearing times of the activity executor attributes, and the structural relationship between the frequent activity blocks and the frequent combinations in the activity blocks is obtained. According to the behavior pattern mining method, some fixed behavior patterns in the unstructured business process are mined from the point of cooperation, and the behavior pattern mining method is of great significance in effective analysis of the unstructured business process.

Description

technical field [0001] The invention belongs to the field of process mining in business process management, and in particular relates to a method for mining behavior patterns of unstructured business process logs based on entity track pairing. Background technique [0002] In the field of business process management (BPM), the goal of process mining is to improve processes, where common product development processes are often unstructured because they are infrequent (compared to production processes) and rely on creating power and problem-solving abilities. For example, mining event logs from the SCM (Software Configuration Management) system, and then performing process mining on these logs, it is found that the process models obtained using traditional process mining methods are all "spaghetti" style, so this type of business process is often Known as an unstructured business process. [0003] It is difficult to analyze the "spaghetti"-like process model obtained by mini...

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Problems solved by technology

[0003] It is difficult to analyze the "spaghetti"-like process model obtained by mining unstructured business processes, so people often use traditional heuristic mining algorithms to filter out low-frequency behaviors to obtain process models, or use fuzzy mining to obtain process models. Algorithms abstract and extract the resulting complex process model, but the resulting model is still difficult to understand

This phenomenon is not caused by the mining algorithm, but because the process is independently decided by the executors, so their degree of structure itself is low, and it is precisely because of these autonomous behaviors that the "spaghetti" type Generation of Process Model

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