Workflow mining method based on subsequent tasks

Abstract

The invention discloses a workflow mining method based on subsequent tasks. The workflow mining based on an event log takes the event log as an input and takes a workflow model described by a Petri network as an output result; by the method, event types are introduced to ensure that the workflow log comprises a subsequent task of the current task, and the subsequent task refers to an aggregate of the tasks to which an execute permission is transferred after the current task is finished; and the method comprises the following steps of: (1) setting an initial value for a workflow process model to be mined; (2) analyzing the event log W, and calculating a task set TW, an initial task and an end task TO; (3) calling a relation Preprocess process to obtain a causal relation matrix M2 and a potential concurrency relation and concurrency relation matrix M3; and (4) calculating an initial task relation set XW according to the matrixes M2 and M3. By the invention, an integrated workflow mining method based on the subsequent tasks is formed.

Description

technical field [0001] The invention belongs to the technical field of workflow, in particular to a workflow mining technology in the technical field of workflow, which is a technology for mining a workflow process model from a workflow log. Background technique [0002] A workflow process is defined as the whole or part of a business process that transfers documents, information, or activities from one participant to another according to a series of procedures or rules. A workflow system is an automated system for centrally managing workflows. Most information systems now use defined workflow models to describe task relationships and maintain the entire business process. However, with more and more business processes and more and more complex individual business processes, the workflow model will inevitably have inefficiencies and even errors. Therefore, it is necessary to monitor and improve the business process, and these requirements need to obtain the real behavior of...

AI Technical Summary

Problems solved by technology

Although these methods can mine a part of the workflow model, it is difficult or even impossible to mine the implicit causal dependencies and implicit places.

In the above event log-based workflow mining method, α ++ The mining ability of this method is the strongest. Although this method can mine SWF structure, short loop structure and most of the implicit causal dependency structures, it cannot deal with the implicit place structure, and α ++ The method needs to adopt complex logical task relationship analysis when mining the implicit causal dependency structure, which greatly increases the complexity of the method

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