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Concept Description Vectors and the 20 Question Game

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Intelligent Information Processing and Web Mining

Part of the book series: Advances in Soft Computing ((AINSC,volume 31))

Abstract

Knowledge of properties that are applicable to a given object is a necessary prerequisite to formulate intelligent question. Concept description vectors provide simplest representation of this knowledge, storing for each object information about the values of its properties. Experiments with automatic creation of concept description vectors from various sources, including ontologies, dictionaries, encyclopedias and unstructured text sources, are described. Information collected in this way is used to formulate questions that have high discriminating power in the twenty questions game.

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References

  1. J. Weizenbaum, Computer Power and Human Reason: From Judgment to Calculation. W. H. Freeman & Co. New York, NY, USA 1976.

    Google Scholar 

  2. See transcripts at: http://www.loebner.net/Prizef/loebner-prize.html

    Google Scholar 

  3. H. Brandt-Pook, G.A. Fink, B. Hildebrandt, F. Kummert, and G. Sagerer. A Robust Dialogue System for Making an Appointment. In: Int. Conf. on Spoken Language Processing, Vol. 2, pp. 693–696, Philadelphia, PA, USA, 1996.

    Article  Google Scholar 

  4. G. Hickok, D. Poeppel, Dorsal and ventral streams: A new framework for understanding aspects of the functional anatomy of language. Cognition, 92: 67–99, 2004.

    Article  Google Scholar 

  5. W.B. Dolan, L. Vanderwende and S. Richardson, Automatically Deriving Structured Knowledge Base from On-line Dictionaries. PACLING 93, Pacific Assoc. for Computational Linguistics, pp. 5–14, 1993.

    Google Scholar 

  6. S. Richardson, Determining Similarity and Inferring Relations in a Lexical Knowledge Base. Ph.D. thesis, 187 p, The City University of New York, 1997.

    Google Scholar 

  7. L. Vanderwende, The Analysis of Noun Sequences using Semantic Information Extracted from On-Line Dictionaries. Ph.D. thesis, 312 p, Georgetown University, 1995.

    Google Scholar 

  8. C. Fellbaum (Ed), WordNet. An Electronic Lexical Database. MIT Press, 1998.

    Google Scholar 

  9. See www.20q.net

    Google Scholar 

  10. T. Kohonen, Self-Organizing Maps. Springer-Verlag, Heidelberg Berlin, 1995.

    Google Scholar 

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© 2005 Springer-Verlag Berlin Heidelberg

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Duch, W., Szymański, J., Sarnatowicz, T. (2005). Concept Description Vectors and the 20 Question Game. In: Kłopotek, M.A., Wierzchoń, S.T., Trojanowski, K. (eds) Intelligent Information Processing and Web Mining. Advances in Soft Computing, vol 31. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32392-9_5

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  • DOI: https://doi.org/10.1007/3-540-32392-9_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25056-2

  • Online ISBN: 978-3-540-32392-1

  • eBook Packages: EngineeringEngineering (R0)

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