• DocumentCode
    1840151
  • Title

    Business Process Mining Based on Simulated Annealing

  • Author

    Song, Wei ; Liu, ShaoZhuo ; Liu, Qiang

  • Author_Institution
    Sch. of Software, Tsinghua Univ., Beijing
  • fYear
    2008
  • fDate
    18-21 Nov. 2008
  • Firstpage
    725
  • Lastpage
    730
  • Abstract
    In order to identify business processes effectively, historical data, such as event log, can be used as a base to retrieve abstract process model. The result of process mining can provide necessary information to deploy process-aware information systems. Process structure patterns disclosing the relationship among activities is one of the most important aspects. To retrieve the process model comprehensively and quickly, this paper propose a simulated annealing process mining approach to address this issue. Main contribution of the work includes : (1) Apply the simulated annealing approach under the setting of process mining. (2)Represent events as "causal matrix". (3) Evaluate the mining result with a quantitative measurement, incorporate the ideas above into existing simulated annealing algorithm to form an integrated solution. We give experimental results which created by the ProM, a platform for business process mining, with the data it provides.
  • Keywords
    business data processing; data mining; simulated annealing; business process mining; process-aware information systems; simulated annealing; Algorithm design and analysis; Computational modeling; Computer simulation; Discrete event simulation; Genetic algorithms; Hidden Markov models; Information retrieval; Information systems; PROM; Simulated annealing; Petri-net; process mining; simulate annealing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Young Computer Scientists, 2008. ICYCS 2008. The 9th International Conference for
  • Conference_Location
    Hunan
  • Print_ISBN
    978-0-7695-3398-8
  • Electronic_ISBN
    978-0-7695-3398-8
  • Type

    conf

  • DOI
    10.1109/ICYCS.2008.279
  • Filename
    4709063