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Analogy as an Organizational Principle in the Construction of Large Knowledge-Bases

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Computational Approaches to Analogical Reasoning: Current Trends

Part of the book series: Studies in Computational Intelligence ((SCI,volume 548))

Abstract

A capacity for analogy is an excellent acid test for the quality of a knowledge-base. A good knowledge-base should be balanced and coherent, so that its high-level generalities are systematically reflected in a variety of lower-level specializations. As such, we can expect a rich, well-structured knowledge-base to support a greater diversity of analogies than one that is imbalanced, disjoint or impoverished. We argue here that the converse is also true: when choosing from a large pool of candidate propositions, in which many propositions are invalid because they are extracted automatically from corpora or volunteered by untrained web-users, we should prefer those that are most likely to enhance the analogical productivity of the knowledge-base. We present a simple and efficient means of finding potential analogies within a large knowledge-base, using a corpus-constrained notion of pragmatic comparability rather than the typically less-constrained notion of semantic similarity. This allows us to empirically demonstrate, in the context of a substantial knowledge-base of simple generalizations automatically extracted from the Google n-grams, that knowledge acquisition proceeds at a significantly faster pace when candidate additions are prioritized according to their analogical potential.

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Acknowledgments

This research was supported by the WCU (World Class University) program under the National Research Foundation of Korea, and funded by the Ministry of Education, Science and Technology of Korea (Project No: R31-30007).

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Authors and Affiliations

  1. Web Science and Technology Division, KAIST, Yuseong, Korea

    Tony Veale & Guofu Li

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  1. Tony Veale
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  2. Guofu Li
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Correspondence to Tony Veale .

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Editors and Affiliations

  1. IRIT-CNRS, University of Toulouse, Toulouse, France

    Henri Prade

  2. IRIT-CNRS, University of Toulouse, Toulouse, France

    Gilles Richard

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Veale, T., Li, G. (2014). Analogy as an Organizational Principle in the Construction of Large Knowledge-Bases. In: Prade, H., Richard, G. (eds) Computational Approaches to Analogical Reasoning: Current Trends. Studies in Computational Intelligence, vol 548. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54516-0_4

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  • DOI: https://doi.org/10.1007/978-3-642-54516-0_4

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-54515-3

  • Online ISBN: 978-3-642-54516-0

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