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Learning Block-Preserving Outerplanar Graph Patterns and Its Application to Data Mining

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5194))

Abstract

An outerplanar graph is a planar graph which can be embedded in the plane in such a way that all of vertices lie on the outer boundary. Many chemical compounds are known to be expressed by outerplanar graphs. We proposed a block preserving outerplanar graph pattern (bpo- graph pattern, for short) as a graph pattern common to a set of outerplanar graphs like a dataset of chemical compounds. In this paper, firstly we give a polynomial time algorithm for finding a minimally generalized bpo- graph pattern explaining a given set of outerplanar graphs. Secondly we give a pattern mining algorithm for enumerating all maximal frequent bpo- graph patterns in a set of outerplanar graphs. Finally, in order to show the performance of the pattern mining algorithm, we report experimental results on chemical datasets.

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Filip Železný Nada Lavrač

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Yamasaki, H., Sasaki, Y., Shoudai, T., Uchida, T., Suzuki, Y. (2008). Learning Block-Preserving Outerplanar Graph Patterns and Its Application to Data Mining. In: Železný, F., Lavrač, N. (eds) Inductive Logic Programming. ILP 2008. Lecture Notes in Computer Science(), vol 5194. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85928-4_25

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  • DOI: https://doi.org/10.1007/978-3-540-85928-4_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85927-7

  • Online ISBN: 978-3-540-85928-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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