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Using n-grams for the Automated Clustering of Structural Models

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SOFSEM 2017: Theory and Practice of Computer Science (SOFSEM 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10139))

Abstract

Model comparison and clustering are important for dealing with many models in data analysis and exploration, e.g. in domain model recovery or model repository management. Particularly in structural models, information is captured not only in model elements (e.g. in names and types) but also in the structural context, i.e. the relation of one element to the others. Some approaches involve a large number of models ignoring the structural context of model elements; others handle very few (typically two) models applying sophisticated structural techniques. In this paper we address both aspects and extend our previous work on model clustering based on vector space model, with a technique for incorporating structural context in the form of n-grams. We compare the n-gram accuracy on two datasets of Ecore metamodels in AtlanMod Zoo: small random samples using up to trigrams and a larger one (\({\sim }\)100 models) up to bigrams.

The research leading to these results has been funded by EU programme FP7-NMP-2013-SMALL-7 under grant agreement number 604279 (MMP).

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Notes

  1. 1.

    https://cran.r-project.org/.

  2. 2.

    http://web.emn.fr/x-info/atlanmod/index.php?title=Ecore.

  3. 3.

    https://www.eclipse.org/emf/compare/.

  4. 4.

    http://www.eclipse.org/modeling/emf/.

  5. 5.

    https://cran.r-project.org/package=lsa.

  6. 6.

    https://cran.r-project.org/package=dynamicTreeCut.

  7. 7.

    https://github.com.

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Author information

Authors and Affiliations

  1. Eindhoven University of Technology, 5600 MB, Eindhoven, The Netherlands

    Önder Babur & Loek Cleophas

  2. Stellenbosch University, Matieland, 7602, South Africa

    Loek Cleophas

Authors
  1. Önder Babur
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  2. Loek Cleophas
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Corresponding author

Correspondence to Önder Babur .

Editor information

Editors and Affiliations

  1. TU Dortmund , Dortmund, Germany

    Bernhard Steffen

  2. TU Dresden , Dresden, Germany

    Christel Baier

  3. Eindhoven University of Technology , Eindhoven, The Netherlands

    Mark van den Brand

  4. Alpen Adria University Klagenfurt , Klagenfurt, Austria

    Johann Eder

  5. Lero - Irish Software Research Center , Limerick, Ireland

    Mike Hinchey

  6. Lero - Irish Software Research Center , Limerick, Ireland

    Tiziana Margaria

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Babur, Ö., Cleophas, L. (2017). Using n-grams for the Automated Clustering of Structural Models. In: Steffen, B., Baier, C., van den Brand, M., Eder, J., Hinchey, M., Margaria, T. (eds) SOFSEM 2017: Theory and Practice of Computer Science. SOFSEM 2017. Lecture Notes in Computer Science(), vol 10139. Springer, Cham. https://doi.org/10.1007/978-3-319-51963-0_40

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  • DOI: https://doi.org/10.1007/978-3-319-51963-0_40

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-51962-3

  • Online ISBN: 978-3-319-51963-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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