文章基本信息

标题：PROCESS DISCOVERY: A NEW METHOD FITTED TO BIG EVENT LOGS
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作者：SOUHAIL BOUSHABA ; MOHAMMAD ISSAM KABBAJ ; FATIMA-ZAHRA BELOUADHA 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2015
卷号：77
期号：1
出版社：Journal of Theoretical and Applied
摘要：Business process discovery is a research field assembling techniques that allow representation of a business process, taking as input an event log where process data are stored. Several advances have been made in process discovery, but as data volume starts to weight considerably, improvement of discovery methods is crucial to follow up. In this paper, we discuss our new method, inspired from image processing techniques. Adapted to voluminous data logs, our method relies on generation of a Petri net using a matrix representation of data. The principal idea behind our approach consists of using several concepts: partial & feature blocks, filters as well as the adaptation of combinatory logic concepts to process mining in the perspective of extracting a business process model from a big event log.
关键词：Process Mining; Business Process Management; Process Discovery; Distributed Algorithm