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Efficient Retrieval of Similar Business Process Models Based on Structure

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  • Conference paper
On the Move to Meaningful Internet Systems: OTM 2011 (OTM 2011)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7044))

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Abstract

With the business process management technology being more widely used, there are more and more business process models, which are typically graphical. How to query such a large number of models efficiently is challenging. In this paper, we solve the problem of querying similar models efficiently based on structure. We use an index named TaskEdgeIndex for query processing. During query processing, we estimate the minimum number of edges that must be contained according to the given similarity threshold, and then obtain the candidate models through the index. Then we compute the similarity between the query condition model and every candidate model based on graph structure by using maximum common edge subgraph based similarity, and discard the candidate models that actually do not satisfy the similarity requirement. Since the number of candidate models is always much smaller than the size of repositories, the query efficiency is improved.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Technology, Tsinghua University, China

    Tao Jin

  2. School of Software, Tsinghua University, China

    Tao Jin, Jianmin Wang & Lijie Wen

Authors
  1. Tao Jin
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  2. Jianmin Wang
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  3. Lijie Wen
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Editor information

Editors and Affiliations

  1. STAR Lab, Vrije Universiteit Brussel (VUB), Bldg G/10, Pleinlaan 2, 1050, Brussel, Belgium

    Robert Meersman

  2. DEBII, Curtin University of Technology, Technology Park, De Laeter Way, 6102, Bentley, WA, Australia

    Tharam Dillon

  3. Facultad de Informática, Universidad Politécnica de Madrid, Campus de Montegancedo S/N, 28660, Boadilla del Monte, Madrid, Spain

    Pilar Herrero

  4. Smeal College of Business, Pennsylvania State University, University Park, PA 16802, U.S.A.

    Akhil Kumar

  5. Institute of Databases and Information Systems, Ulm University, Germany

    Manfred Reichert

  6. City University of Hong Kong, Hong Kong

    Li Qing

  7. National University of Singapore (NUS), Singapore

    Beng-Chin Ooi

  8. Dipartemento Tecnologie dell’Informazione, Universitá degli Studi di Milano, Via Bramante 65, 26013, Crema, Italy

    Ernesto Damiani

  9. VU Station B #1829, Vanderbilt University, 2015 Terrace Place, TN 37203, Nashville, USA

    Douglas C. Schmidt

  10. Virginia Tech, 24060, Blacksburg, VA, USA

    Jules White

  11. Digital Enterprise Research Institute (DERI), National University of Ireland, IDA Business Park, Lower Dangan, Galway, Ireland

    Manfred Hauswirth

  12. Kno.e.sis Center, Wright State University, Dayton, Ohio, USA

    Pascal Hitzler

  13. IBM India Research Lab, 4, Block C, Institutional Area, Vasant Kunj, 110 070, New Delhi, India

    Mukesh Mohania

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Jin, T., Wang, J., Wen, L. (2011). Efficient Retrieval of Similar Business Process Models Based on Structure. In: Meersman, R., et al. On the Move to Meaningful Internet Systems: OTM 2011. OTM 2011. Lecture Notes in Computer Science, vol 7044. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25109-2_5

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  • DOI: https://doi.org/10.1007/978-3-642-25109-2_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25108-5

  • Online ISBN: 978-3-642-25109-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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