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Structural Change Pattern Mining Based on Constrained Maximal k-Plex Search

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Discovery Science (DS 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7569))

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Abstract

We discuss in this paper a problem of mining structural change patterns. Given a pair of graphs before and after some change, a structural change pattern is extracted as a vertex set X which is pseudo-independent set before the change but a pseudo-clique after the change. In order to detect this kind of patterns more interesting, X is particularly required to have many outgoing edges from X before the change, while to have few outgoing edges after the change. We formalize such an X as a maximal k-plex in the combined graph defined from the given graphs. An effective algorithm for extracting them is designed as a constrained maximal k-plex enumerator with a pruning mechanism based on right candidate control. Our experimental results show an example of structural change pattern actually detected. Moreover, it is shown that the pruning mechanism and the use of combined graph are very effective for efficient computation.

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Okubo, Y., Haraguchi, M., Tomita, E. (2012). Structural Change Pattern Mining Based on Constrained Maximal k-Plex Search. In: Ganascia, JG., Lenca, P., Petit, JM. (eds) Discovery Science. DS 2012. Lecture Notes in Computer Science(), vol 7569. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33492-4_23

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  • DOI: https://doi.org/10.1007/978-3-642-33492-4_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33491-7

  • Online ISBN: 978-3-642-33492-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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