Mining Based on Learning from Process Change Logs

C. Li, M.U. Reichert, Andreas Wombacher

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

7 Citations (Scopus)


In today’s dynamic business world economic success of an enterprise increasingly depends on its ability to react to internal and external changes in a quick and flexible way. In response to this need, process-aware information systems (PAIS) emerged, which support the modeling, orchestration and monitoring of business processes. Recently, a new generation of flexible PAIS was introduced, which additionally allows for dynamic process changes. This, in turn, leads to a large number of process variants, which are created from the same original model, but might slightly differ from each other. This paper deals with issues related to the mining of such process variant collections. Our overall goal is to learn from process changes and to merge the resulting model variants into a generic process model in the best possible way. By adopting this generic process model in the PAIS, future costs of process change and need for process adaptations will decrease. We compare process variant mining with conventional process mining techniques, and show that it is additionally needed to learn from process changes.
Original languageUndefined
Title of host publicationBusiness Process Magagement Workshops: BPM 2008 International Workshops
EditorsDanilo Ardagna, Massimo Mecella, Jian Yang
Place of PublicationBerlin
Number of pages13
ISBN (Print)978-3-642-00327-1
Publication statusPublished - 2008
EventBusiness Process Magagement Workshops: BPM 2008 International Workshops - Milano, Italy
Duration: 1 Sept 20084 Sept 2008

Publication series

NameLecture Notes in Business Information Processing
PublisherSpringer Verlag
ISSN (Print)1865-1348


WorkshopBusiness Process Magagement Workshops: BPM 2008 International Workshops
Other1-4 September 2008


  • METIS-264069
  • SCS-Services
  • EWI-16157
  • IR-68158

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