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(Missing) Concept Discovery in Heterogeneous Information Networks

(Missing) Concept Discovery in Heterogeneous Information Networks

  • Tobias Kötter5 &
  • Michael R. Berthold5 
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Part of the Lecture Notes in Computer Science book series (LNAI,volume 7250)

Abstract

This article proposes a new approach to extract existing (or detect missing) concepts from a loosely integrated collection of information units by means of concept graph detection. Thereby a concept graph defines a concept by a quasi bipartite sub-graph of a bigger network with the members of the concept as the first vertex partition and their shared aspects as the second vertex partition. Once the concepts have been extracted they can be used to create higher level representations of the data. Concept graphs further allow the discovery of missing concepts, which could lead to new insights by connecting seemingly unrelated information units.

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Authors and Affiliations

  1. Nycomed-Chair for Bioinformatics and Information Mining, University of Konstanz, 78484, Konstanz, Germany

    Tobias Kötter & Michael R. Berthold

Authors
  1. Tobias Kötter
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  2. Michael R. Berthold
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Editors and Affiliations

  1. Department of Computer and Information Science, University of Konstanz, Konstanz, Germany

    Michael R. Berthold

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Kötter, T., Berthold, M.R. (2012). (Missing) Concept Discovery in Heterogeneous Information Networks. In: Berthold, M.R. (eds) Bisociative Knowledge Discovery. Lecture Notes in Computer Science(), vol 7250. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31830-6_16

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