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Trace Alignment in Process Mining: Opportunities for Process Diagnostics

  • R. P. Jagadeesh Chandra Bose
  • Wil van der Aalst
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6336)

Abstract

Process mining techniques attempt to extract non-trivial knowledge and interesting insights from event logs. Process mining provides a welcome extension of the repertoire of business process analysis techniques and has been adopted in various commercial BPM systems (BPM∣one, Futura Reflect, ARIS PPM, Fujitsu, etc.). Unfortunately, traditional process discovery algorithms have problems dealing with less-structured processes. The resulting models are difficult to comprehend or even misleading. Therefore, we propose a new approach based on trace alignment. The goal is to align traces in a way that event logs can be explored easily. Trace alignment can be used in a preprocessing phase where the event log is investigated or filtered and in later phases where detailed questions need to be answered. Hence, it complements existing process mining techniques focusing on discovery and conformance checking.

Keywords

Guide Tree Agglomerative Hierarchical Cluster Process Instance Information Score Progressive Alignment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • R. P. Jagadeesh Chandra Bose
    • 1
    • 2
  • Wil van der Aalst
    • 1
  1. 1.Department of Mathematics and Computer ScienceUniversity of TechnologyEindhovenThe Netherlands
  2. 2.Philips HealthcareBestThe Netherlands

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