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A Framework for Integrating Deep and Shallow Semantic Structures in Text Mining

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2773))

Abstract

Recent work in knowledge representation undertaken as part of the Semantic Web initiative has enabled a common infrastructure (Resource Description Framework (RDF) and RDF Schema) for sharing knowledge of ontologies and instances. In this paper we present a framework for combining the shallow levels of semantic description commonly used in MUC-style information extraction with the deeper semantic structures available in such ontologies. The framework is implemented within the PIA project software called Ontology Forge. Ontology Forge offers a server-based hosting environment for ontologies, a server-side information extraction system for reducing the effort of writing annotations and a many-featured ontology/annotation editor. We discuss the knowledge framework, some features of the system and summarize results from extended named entity experiments designed to capture instances in texts using support vector machine software.

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Author information

Authors and Affiliations

  1. National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo, 101-8430, Japan

    Nigel Collier, Koichi Takeuchi, Ai Kawazoe, Tony Mullen & Tuangthong Wattarujeekrit

Authors
  1. Nigel Collier
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  2. Koichi Takeuchi
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  3. Ai Kawazoe
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  4. Tony Mullen
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  5. Tuangthong Wattarujeekrit
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Editor information

Editors and Affiliations

  1. Computing Laboratory, Oxford University, Parks Road, OXI 3QD, United Kingdom

    Vasile Palade

  2. Intelligent Systems and Signal Processing Labs, Moulsecoomb, University of Brighton, BN2 4GJ, Brighton, United Kingdom

    Robert J. Howlett

  3. Knowledge-Based Intelligent Engineering Systems Centre, Mawson Lakes, University of South Australia, 5095, Adelaide, SA, Australia

    Lakhmi Jain

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© 2003 Springer-Verlag Berlin Heidelberg

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Collier, N., Takeuchi, K., Kawazoe, A., Mullen, T., Wattarujeekrit, T. (2003). A Framework for Integrating Deep and Shallow Semantic Structures in Text Mining. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45224-9_110

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  • DOI: https://doi.org/10.1007/978-3-540-45224-9_110

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40803-1

  • Online ISBN: 978-3-540-45224-9

  • eBook Packages: Springer Book Archive

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