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Author

Song, Minseok
Business Process Intelligence(BPI) Lab
Research Interests
  • Process mining

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자취 군집화를 통한 프로세스 마이닝의 성능 개선

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Title
자취 군집화를 통한 프로세스 마이닝의 성능 개선
Other Titles
Improving Process Mining with Trace Clustering
Author
Song, MinseokGunther, C.W.van der Aalst, W.M.P.Jung, Jae-Yoon
Keywords
Process Mining; Trace Clustering; Workflow; Data Mining; SOM
Issue Date
200812
Publisher
대한산업공학회
Citation
대한산업공학회지, v.34, no.4, pp.460 - 469
Abstract
Process mining aims at mining valuable information from process execution results (called “event logs”). Even though process mining techniques have proven to be a valuable tool, the mining results from real process logs are usually too complex to interpret. The main cause that leads to complex models is the diversity of process logs. To address this issue, this paper proposes a trace clustering approach that splits a process log into homogeneous subsets and applies existing process mining techniques to each subset. Based on log profiles from a process log, the approach uses existing clustering techniques to derive clusters. Our approach are implemented in ProM framework. To illustrate this, a real-life case study is also presented.
URI
http://scholarworks.unist.ac.kr/handle/201301/4604
ISSN
1225-0988
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