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Knowledge-Rich Contexts Discovery

  • Conference paper
Advances in Artificial Intelligence (Canadian AI 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3060))

Abstract

Within large corpora of texts, Knowledge-Rich Contexts (KRCs) are a subset of sentences containing information that would be valuable to a human for the construction of a knowledge base. The entry point to the discovery of KRCs is the automatic identification of Knowledge Patterns (KPs) which are indicative of semantic relations. Machine readable dictionary serves as our starting point for investigating the types of knowledge embodied in definitions and some associated KPs. We then move toward corpora analysis and discuss issues of generality/specificity as well as KPs efficiency. We suggest an expansion of the lexical-syntactic definitions of KPs to include a semantic dimension, and we briefly present a tool for knowledge acquisition, SeRT, which allows user such flexible definition of KPs for automatic discovery of KRCs.

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Author information

Authors and Affiliations

  1. Research Center for Language Technology, National Research Center of Canada, Gatineau, Québec, Canada

    Caroline Barrière

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  1. Caroline Barrière
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Editor information

Editors and Affiliations

  1. University of Windsor, 401 Sunset Avenue, N9B 3P4, Windsor, Ontario, Canada

    Ahmed Y. Tawfik

  2. School of Computer Science, University of Windsor, Windsor, Ontario,  

    Scott D. Goodwin

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© 2004 Springer-Verlag Berlin Heidelberg

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Barrière, C. (2004). Knowledge-Rich Contexts Discovery. In: Tawfik, A.Y., Goodwin, S.D. (eds) Advances in Artificial Intelligence. Canadian AI 2004. Lecture Notes in Computer Science(), vol 3060. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24840-8_14

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  • DOI: https://doi.org/10.1007/978-3-540-24840-8_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22004-6

  • Online ISBN: 978-3-540-24840-8

  • eBook Packages: Springer Book Archive

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