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Self-learning web question answering system

Published: 19 May 2004 Publication History

Abstract

While being quite successful in providing keyword based access to web pages, commercial search portals, such as Google, Yahoo, AltaVista, and AOL, still lack the ability to answer questions expressed in a natural language. In this paper, we present a probabilistic approach to automated question answering on the Web. Our approach is based on pattern matching and answer triangulation. By taking advantage of the redundancy inherent in the Web, each answer found by the system is triangulated (confirmed or disconfirmed) against other possible answers. Our approach is entirely self-learning: it does not involve any linguistic resources, nor it does require any manual tuning. Thus, the propose approach can easily be replicated in other information systems with large redundancy.

References

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Agichtein, E., Lawrence, S., Gravano, L. Learning Search Engine Specific Query Transformations for Question Answering. 10th WWW Conference, 2001.
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Dumais, S., Banko, M., Brill, E., Lin, J., and Ng, A. Web Question Answering: Is More Always Better? ACM Conference on Information Retrieval, 2002.
[3]
Radev, D., Fan, W., Qi, H., Wu, H., Grewal, A. Probabilistic Question Answering on the Web. 11th WWW Conf. 2002.
[4]
Surdeanu, M., Moldovan, D. and Harabagiu, S. Performance Analysis of a Distributed Question Answering System', IEEE Transactions on Parallel and Distributed Systems, June 2002.
[5]
Voorhees, E. and Harman, D., Eds. Proceedings of the Tenth Text REtrieval Conference (TREC 2001).
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Brill, E. Transformation-based error-driven learning and natural language processing: A case study in part of speech tagging. Computational Linguistics, 21(4):543--566, 1995.
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Ravichandran, D., & Hovy, E. Learning surface text patterns for a question answering system. In Proceedings of the 40th Annual Meeting of the ACL, pages 41--47.

Cited By

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  • (2013)Strategies for Improving the Efficacy of Fusion Question Answering SystemsPrinciples and Applications of Business Intelligence Research10.4018/978-1-4666-2650-8.ch013(181-198)Online publication date: 2013
  • (2011)Strategies for Improving the Efficacy of Fusion Question Answering SystemsInternational Journal of Business Intelligence Research10.4018/jbir.20110101042:1(46-63)Online publication date: 1-Jan-2011

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  1. Self-learning web question answering system

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    cover image ACM Conferences
    WWW Alt. '04: Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
    May 2004
    532 pages
    ISBN:1581139128
    DOI:10.1145/1013367
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 19 May 2004

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    View all
    • (2013)Strategies for Improving the Efficacy of Fusion Question Answering SystemsPrinciples and Applications of Business Intelligence Research10.4018/978-1-4666-2650-8.ch013(181-198)Online publication date: 2013
    • (2011)Strategies for Improving the Efficacy of Fusion Question Answering SystemsInternational Journal of Business Intelligence Research10.4018/jbir.20110101042:1(46-63)Online publication date: 1-Jan-2011

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