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International Symposium on Intelligent Data Analysis

IDA 2012: Advances in Intelligent Data Analysis XI pp 90–102Cite as

Online Techniques for Dealing with Concept Drift in Process Mining

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7619))

Abstract

Concept drift is an important concern for any data analysis scenario involving temporally ordered data. In the last decade Process mining arose as a discipline that uses the logs of information systems in order to mine, analyze and enhance the process dimension. There is very little work dealing with concept drift in process mining. In this paper we present the first online mechanism for detecting and managing concept drift, which is based on abstract interpretation and sequential sampling, together with recent learning techniques on data streams.

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Author information

Authors and Affiliations

  1. Universitat Politècnica de Catalunya, Barcelona, Spain

    Josep Carmona & Ricard Gavaldà

Authors
  1. Josep Carmona
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  2. Ricard Gavaldà
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Editor information

Editors and Affiliations

  1. Department of Information and Computer Science, Aalto University School of Science, P.O. Box 15400, 00076, Aalto, Finland

    Jaakko Hollmén

  2. Department of Computer Science, Ostfalia University of Applied Sciences, Salzdahlumer Straße 46/48, 38302, Wolfenbüttel, Germany

    Frank Klawonn

  3. School of Information Systems, Computing and Mathematics, Brunel University, UB8 3PH, Uxbridge, Middlesex, UK

    Allan Tucker

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Carmona, J., Gavaldà, R. (2012). Online Techniques for Dealing with Concept Drift in Process Mining. In: Hollmén, J., Klawonn, F., Tucker, A. (eds) Advances in Intelligent Data Analysis XI. IDA 2012. Lecture Notes in Computer Science, vol 7619. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34156-4_10

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  • DOI: https://doi.org/10.1007/978-3-642-34156-4_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34155-7

  • Online ISBN: 978-3-642-34156-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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