Authors:
Yaguang Sun
and
Bernhard Bauer
Affiliation:
University of Augsburg, Germany
Keyword(s):
Business Process Mining, Multi-label Case Classification, Sequential Pattern Mining, Business Process Extension.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Data Engineering
;
Data Mining
;
Databases and Information Systems Integration
;
Enterprise Information Systems
;
Health Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Management
;
Ontologies and the Semantic Web
;
Sensor Networks
;
Signal Processing
;
Society, e-Business and e-Government
;
Soft Computing
;
Web Information Systems and Technologies
Abstract:
In the last years business process mining has become a wide research area. However, existing process mining
techniques encounter challenges while dealing with event logs stemming from highly flexible environments
because such logs contain a large amount of different behaviors. As a result, inaccurate and wrong analysis
results might be obtained. In this paper we propose a case (a case is an instance of the business process)
classification technique which is able to combine domain experts knowledge for classifying cases so that
each group is calculated containing the cases with similar behaviors. By applying existing process mining
techniques on the cases for each group, more meaningful and accurate analysis results can be obtained.