• DocumentCode
    2368997
  • Title

    Process mining for semantic business process modeling

  • Author

    Lautenbacher, Florian ; Bauer, Bernhard ; Förg, Sebastian

  • Author_Institution
    Programming Distrib. Syst. Lab., Univ. of Augsburg, Augsburg, Germany
  • fYear
    2009
  • fDate
    1-4 Sept. 2009
  • Firstpage
    45
  • Lastpage
    53
  • Abstract
    Business processes are captured by models that serve as a basis for communication and training purposes, but this modeling is still a time consuming manual job. Semantic annotation of process models in combination with AI planning approaches can contribute to solve this drawback enabling an automatic creation of process models. But the semantic annotated process fragments necessary for starting the planning are often missing at all or not up-to-date anymore. Therefore, this work describes an approach for the semantic annotation and semantic-based planning of process models and introduces Cystid, an integration of Process Mining algorithms and semantic-based planning.
  • Keywords
    business process re-engineering; data mining; planning (artificial intelligence); process planning; programming language semantics; specification languages; AI planning; Cystid algorithm; process mining; semantic business process modeling; semantic process annotation; semantic-based process planning; Artificial intelligence; Business communication; Companies; Engines; Enterprise resource planning; Information systems; Libraries; Management training; Ontologies; Process planning; Process Mining; Process Models; SBPM;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Enterprise Distributed Object Computing Conference Workshops, 2009. EDOCW 2009. 13th
  • Conference_Location
    Auckland
  • Print_ISBN
    978-1-4244-5563-8
  • Type

    conf

  • DOI
    10.1109/EDOCW.2009.5332017
  • Filename
    5332017