Business process online compliance prediction method and system based on bidirectional GRU neural network
A technology of neural network and business process, applied in the field of online compliance prediction of business process based on bidirectional GRU neural network, can solve problems such as no longer applicable
Active Publication Date: 2020-05-22
ZHEJIANG UNIVERSITY OF MEDIA AND COMMUNICATIONS
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Problems solved by technology
However, with the continuous development of the demand for real-time monitoring of business processes, traditional offline compliance checks are no longer applicable. Researchers have proposed online compliance checks of business processes.
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[0039] The specific implementation of the compliance method of the process instance in the online prediction execution based on the event log provided by the present invention is mainly divided into 6 steps (such as figure 1 shown):
[0040] (1) Input the reference process model represented by Petri net (such as figure 2 Shown) the event log data set recorded in the perceived information system (as shown in Table 1), each row in the event log data set corresponds to a detailed event record of an activity involved in a business process execution, that is, a complete Event (denoted by e) information, including the process instance ID where the event is located, the event ID, the timestamp of the event (start time and end time), the event corresponding to the activity name in the reference process model, and the resources required for activity execution and other event attributes and some instance attributes related to the instance, and then add some new attributes based on the...
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The invention discloses a business process online compliance prediction method and system based on a bidirectional GRU neural network, and the method comprises the steps: obtaining an event log data set executed by a historical process, and carrying out preprocessing of the event log data set; obtaining a compliance measurement value of each flow path sigma and the reference flow model M; establishing an online compliance prediction model Y of the process instance being executed and the reference process model M; and comparing the compliance prediction value with a compliance threshold value given by a user to judge whether the executing process instance sigma' is compliant with the reference process model M or not, and determining a compliance threshold value given by the user according to compliance requirements of different processes. The system comprises an event log data set preprocessing module, a compliance calculation module, an event coding module, a feature extraction module,a compliance prediction model training module and an online compliance prediction module.
Description
technical field [0001] The invention belongs to the field of compliance checking in business process mining, and in particular relates to an online compliance prediction method and system for business processes based on a bidirectional GRU neural network. Background technique [0002] The compliance check of business processes is an important means to verify whether the execution of business processes is compliant and to evaluate the effectiveness of process mining algorithms. Typically, the actual execution of a business process is recorded in a process-aware information system in the form of an event log. Therefore, the event log can reflect the behavior during the execution of the business process. Compliance check is to correlate the events in the event log with the activities in the business process model, and find out the similarities and differences between the two through comparison, that is, to find the difference between the behavior described by the process model...
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Login to View More IPC IPC(8): G06Q10/06G06K9/62G06N3/04G06N3/08
CPCG06Q10/0633G06N3/084G06N3/045G06F18/2411Y02P90/30
Inventor 王娇娇俞定国刘畅马小雨沈学文张解放
Owner ZHEJIANG UNIVERSITY OF MEDIA AND COMMUNICATIONS