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European Semantic Web Conference

ESWC 2019: The Semantic Web: ESWC 2019 Satellite Events pp 231–241Cite as

Knowledge-Based Dataless Text Categorization

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11762))

Abstract

Text categorization is an important task due to the rapid growth of online available text data in various domains such as web search snippets, news documents, etc. Traditional supervised methods require a significant amount of training data and manually labeling such data can be very time-consuming and costly. Moreover, in case the text to be labeled is of a specific domain, then only the expensive domain experts are able to fulfill the manual labeling task. This thesis focuses on the problem of missing labeled data and aims to develop a novel and generic model which does not require any labeled training data to categorize text. Instead, it utilizes the semantic similarity between documents and the predefined categories by leveraging graph embedding techniques.

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Notes

  1. 1.

    http://goo.gl/JyCnZq.

  2. 2.

    http://jwebpro.sourceforge.net/data-web-snippets.tar.gz.

  3. 3.

    https://en.wikipedia.org/wiki/Category:Sports.

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Acknowledgement

This thesis is supervised by Prof. Harald Sack and Dr. Lei Zhang.

Author information

Authors and Affiliations

  1. FIZ Karlsruhe, Leibniz Institute for Information Infrastructure, Eggenstein-Leopoldshafen, Germany

    Rima Türker

  2. AIFB, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany

    Rima Türker

Authors
  1. Rima Türker
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Corresponding author

Correspondence to Rima Türker .

Editor information

Editors and Affiliations

  1. Kansas State University, Manhattan, KS, USA

    Pascal Hitzler

  2. Vienna University of Economics and Business, Vienna, Austria

    Sabrina Kirrane

  3. Linköping University, Linköping, Sweden

    Olaf Hartig

  4. Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Victor de Boer

  5. Leibniz Information Centre for Science and Technology University Library (TIB), Hannover, Germany

    Maria-Esther Vidal

  6. University of Bonn, Bonn, Germany

    Maria Maleshkova

  7. Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Stefan Schlobach

  8. Jönköping University, Jönköping, Sweden

    Karl Hammar

  9. F. Hoffmann-La Roche AG, Basel, Switzerland

    Nelia Lasierra

  10. Robert Bosch GmbH, Stuttgart, Germany

    Steffen Stadtmüller

  11. Aalborg University, Aalborg, Denmark

    Katja Hose

  12. IMEC, Ghent University, Ghent, Belgium

    Ruben Verborgh

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Cite this paper

Türker, R. (2019). Knowledge-Based Dataless Text Categorization. In: Hitzler, P., et al. The Semantic Web: ESWC 2019 Satellite Events. ESWC 2019. Lecture Notes in Computer Science(), vol 11762. Springer, Cham. https://doi.org/10.1007/978-3-030-32327-1_42

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  • DOI: https://doi.org/10.1007/978-3-030-32327-1_42

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-32326-4

  • Online ISBN: 978-3-030-32327-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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