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A quality-based terminological reasoning model for text knowledge acquisition

  • Eliciting Knowledge from Textual and Other Sources
  • Conference paper
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Book cover Advances in Knowledge Acquisition (EKAW 1996)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1076))

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Abstract

We introduce a methodology for knowledge acquisition and concept learning from texts that relies upon a quality-based model of terminological reasoning. Concept hypotheses which have been derived in the course of the text understanding process are assigned specific “quality labels” (indicating their significance, reliability, strength). Quality assessment of these hypotheses accounts for conceptual criteria referring to their given knowledge base context as well as linguistic indicators (grammatical constructions, discourse patterns), which led to their generation. We advocate a metareasoning approach which allows for the quality-based evaluation and a bootstrapping-style selection of alternative concept hypotheses as text understanding incrementally proceeds.

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Authors and Affiliations

  1. Computational Linguistics Group, Freiburg University, Europaplatz 1, D-79085, Freiburg, Germany

    Udo Hahn, Manfred Klenner & Klemens Schnattinger

Authors
  1. Udo Hahn
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  2. Manfred Klenner
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  3. Klemens Schnattinger
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Editor information

Nigel Shadbolt Kieron O'Hara Guus Schreiber

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© 1996 Springer-Verlag Berlin Heidelberg

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Hahn, U., Klenner, M., Schnattinger, K. (1996). A quality-based terminological reasoning model for text knowledge acquisition. In: Shadbolt, N., O'Hara, K., Schreiber, G. (eds) Advances in Knowledge Acquisition. EKAW 1996. Lecture Notes in Computer Science, vol 1076. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61273-4_9

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  • DOI: https://doi.org/10.1007/3-540-61273-4_9

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61273-5

  • Online ISBN: 978-3-540-68391-9

  • eBook Packages: Springer Book Archive

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