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From Information Networks to Bisociative Information Networks

From Information Networks to Bisociative Information Networks

  • Tobias Kötter5 &
  • Michael R. Berthold5 
  • Chapter
  • Open Access
  • 8819 Accesses

  • 16 Citations

Part of the Lecture Notes in Computer Science book series (LNAI,volume 7250)

Abstract

The integration of heterogeneous data from various domains without the need for prefiltering prepares the ground for bisociative knowledge discoveries where attempts are made to find unexpected relations across seemingly unrelated domains. Information networks, due to their flexible data structure, lend themselves perfectly to the integration of these heterogeneous data sources. This chapter provides an overview of different types of information networks and categorizes them by identifying several key properties of information units and relations which reflect the expressiveness and thus ability of an information network to model heterogeneous data from diverse domains. The chapter progresses by describing a new type of information network known as bisociative information networks. This kind of network combines the key properties of existing networks in order to provide the foundation for bisociative knowledge discoveries. Finally based on this data structure three different patterns are described that fulfill the requirements of a bisociation by connecting concepts from seemingly unrelated domains.

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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

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  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). From Information Networks to Bisociative 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_3

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