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International Symposium on Methodologies for Intelligent Systems

ISMIS 2017: Foundations of Intelligent Systems pp 435–445Cite as

Semantic Enriched Short Text Clustering

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10352))

Abstract

The paper is devoted to the issue of clustering short texts, which are free answers gathered during brain storming seminars. Those answers are short, often incomplete, and highly biased toward the question, so establishing a notion of proximity between texts is a challenging task. In addition, the number of answers is counted up to hundred instances, which causes sparsity. We present three text clustering methods in order to choose the best one for this specific task, then we show how the method can be improved by a semantic enrichment, including neural-based distributional models and external knowledge resources. The algorithms have been evaluated on the unique seminar’s data sets.

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Notes

  1. 1.

    https://code.google.com/p/word2vec/.

  2. 2.

    http://snowball.tartarus.org/texts/introduction.html.

  3. 3.

    http://norvig.com/spell-correct.html.

  4. 4.

    https://babelfy.io/v1/disambiguate.

  5. 5.

    https://babelnet.io/v3/getSynset.

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Author information

Authors and Affiliations

  1. Warsaw University of Technology, Warsaw, Poland

    Marek Kozlowski & Henryk Rybinski

Authors
  1. Marek Kozlowski
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  2. Henryk Rybinski
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Corresponding author

Correspondence to Marek Kozlowski .

Editor information

Editors and Affiliations

  1. Warsaw University of Technology, Warsaw, Poland

    Marzena Kryszkiewicz

  2. University of Bari Aldo Moro, Bari, Italy

    Annalisa Appice

  3. Institute of Informatics, University of Warsaw, Warsaw, Poland

    Dominik Ślęzak

  4. Faculty of Electronics & Information, Warsaw University of Technology, Warsaw, Poland

    Henryk Rybinski

  5. Institute of Mathematics, Warsaw University, Warsaw, Poland

    Andrzej Skowron

  6. Department of Computer Science, University of North Carolina at Charlotte, North Carolina, USA

    Zbigniew W. Raś

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Kozlowski, M., Rybinski, H. (2017). Semantic Enriched Short Text Clustering. In: Kryszkiewicz, M., Appice, A., Ślęzak, D., Rybinski, H., Skowron, A., Raś, Z. (eds) Foundations of Intelligent Systems. ISMIS 2017. Lecture Notes in Computer Science(), vol 10352. Springer, Cham. https://doi.org/10.1007/978-3-319-60438-1_43

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  • DOI: https://doi.org/10.1007/978-3-319-60438-1_43

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60437-4

  • Online ISBN: 978-3-319-60438-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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