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A Methodology for Mining Document-Enriched Heterogeneous Information Networks

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Discovery Science (DS 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6926))

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Abstract

The paper presents a new methodology for mining heterogeneous information networks, motivated by the fact that, in many real-life scenarios, documents are available in heterogeneous information networks, such as interlinked multimedia objects containing titles, descriptions, and subtitles. The methodology consists of transforming documents into bag-of-words vectors, decomposing the corresponding heterogeneous network into separate graphs and computing structural-context feature vectors with PageRank, and finally constructing a common feature vector space in which knowledge discovery is performed. We exploit this feature vector construction process to devise an efficient classification algorithm. We demonstrate the approach by applying it to the task of categorizing video lectures. We show that our approach exhibits low time and space complexity without compromising classification accuracy.

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Author information

Authors and Affiliations

  1. Dept. of Knowledge Technologies, Jožef Stefan Institute, Jamova cesta 39, 1000, Ljubljana, Slovenia

    Miha Grčar & Nada Lavrač

Authors
  1. Miha Grčar
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  2. Nada Lavrač
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Editor information

Editors and Affiliations

  1. Department of Software Systems, Tampere University of Technology, P. O. Box 553, 33101, Tampere, Finland

    Tapio Elomaa

  2. Department of Information and Computer Science, Aalto University School of Science, P.O. Box 15400, 00076, Aalto, Finland

    Jaakko Hollmén

  3. Helsinki Institute for Information Technology (HIIT), Finland

    Heikki Mannila

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Grčar, M., Lavrač, N. (2011). A Methodology for Mining Document-Enriched Heterogeneous Information Networks. In: Elomaa, T., Hollmén, J., Mannila, H. (eds) Discovery Science. DS 2011. Lecture Notes in Computer Science(), vol 6926. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24477-3_11

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  • DOI: https://doi.org/10.1007/978-3-642-24477-3_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24476-6

  • Online ISBN: 978-3-642-24477-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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