Mining algorithm with time constraint workflow

Abstract

The invention discloses a mining algorithm with a time constraint workflow. The method comprises the following steps of: taking an event log with a time stamp as an input, and taking a mined correct workflow model with time constraints as an output; mining a relationship between the events from the log; deducing and calculating time constraints of the events according to the mined relationship; and finally calling an event relationship model in an alpha algorithm to generate a workflow model without time constraints, and adding the time constraints onto corresponding events to obtain a time constraint workflow model. The mined time constraint workflow model has better completeness, correctness and reliability, is closer to practical workflow process, and is universally suitable for point event logs, interval event logs and mixed type event logs.

Description

technical field [0001] The invention belongs to the field of data mining, in particular to a mining algorithm with time-constrained workflow. Background technique [0002] With the continuous development of Internet technology and cloud computing, workflow-related technologies are playing an increasingly important role in today's information systems. From traditional automated office systems, organizational business management systems to recent service combinations and big data applications in the cloud environment, a large number of workflows are generated, and how to mine high-quality workflow models has become an issue. important technology. [0003] The event log is an important part of the computer information system. It records the events that occur during the execution of the system, as well as relevant information such as the time, operator, and life cycle corresponding to the events. value. The event log is composed of multiple event sequences, each event sequenc...

AI Technical Summary

Problems solved by technology

[0005] Most of the existing process mining technologies are based on event logs that only contain point events or only interval events. However, most event logs in reality are of mixed type. The application of existing process mining technologies to mixed event logs requires log mining. Preprocessing, expanding the point event to an interval event, or deleting the start event or end event of the interval event, cannot guarantee the correct process model to be mined

Images