Abstract
This paper describes a method for definition question answering based on the use of surface text patterns. The method is specially suited to answer questions about person’s positions and acronym’s descriptions. It considers two main steps. First, it applies a sequence-mining algorithm to discover a set of definition-related text patterns from the Web. Then, using these patterns, it extracts a collection of concept-description pairs from a target document database, and applies the sequence-mining algorithm to determine the most adequate answer to a given question. Experimental results on the Spanish CLEF 2005 data set indicate that this method can be a practical solution for answering this kind of definition questions, reaching a precision as high as 84%.
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Ahonen-Myka, H.: Discovery of Frequent Word Sequences in Text Source. In: Hand, D.J., Adams, N.M., Bolton, R.J. (eds.) Pattern Detection and Discovery. LNCS, vol. 2447, p. 180. Springer, Heidelberg (2002)
Cui, H., Kan, M., Chua, T.: Unsupervised Learning of Soft Patterns for Generating Definitions from Online News. In: Proceedings International WWW Conference, New York, USA (2004)
Fleischman, M., Hovy, E., Echihabi, A.: Offline Strategies for Online Question Answering: Answering Question Before they are Asked. In: Proceedings of the ACL 2003, Sapporo, Japan (2003)
García-Hernández, R.A., Martínez-Trinidad, J.F., Carrasco-Ochoa, J.A.: A New Algorithm for Fast Discovery of Maximal Sequential Patterns in a Document Collection. In: Gelbukh, A. (ed.) CICLing 2006. LNCS, vol. 3878, pp. 514–523. Springer, Heidelberg (2006)
Hildebrandt, W., Katz, B., Lin, J.: Answering Definition Questions Using Multiple Knowledge Sources. In: Proceedings of Human Language Technology Conference, Boston, USA (2004)
Montes-y-Gómez, M., Villaseñor-Pineda, L., Pérez-Coutiño, M., Gómez-Soriano, J.M., Sanchis-Arnal, E., Rosso, P.: INAOE-UPV Joint Participation in CLEF 2005: Experiments in Monolingual Question Answering. In: Working Notes of CLEF 2005, Vienna, Austria (2003)
Pantel, P., Ravichandran, D., Hovy, E.: Towards Terascale Knowledge Acquisition. In: Proceedings of the COLING 2004 Conference, Geneva, Switzerland (2004)
Ravichandran, D., Hovy, E.: Learning Surface Text Patterns for a Question Answering System. In: Proceedings of the ACL 2002 Conference, Philadelphia, USA (2002)
Soubbotin, M.M., Soubbotin, S.M.: Patterns of Potential Answer Expressions as Clues to the Right Answer. In: Proceedings of the TREC-10 Conference, Gaithersburg (2001)
Vallin, A., Magnini, B., Giampiccolo, D., Aunimo, L., Ayache, C., Osenova, P., Peñas, A., de Rijke, M., Sacaleanu, B., Santos, D., Sutcliffe, R.F.E.: Overview of the CLEF 2005 multilingual question answering track. In: Peters, C., Gey, F.C., Gonzalo, J., Müller, H., Jones, G.J.F., Kluck, M., Magnini, B., de Rijke, M., Giampiccolo, D. (eds.) CLEF 2005. LNCS, vol. 4022, pp. 307–331. Springer, Heidelberg (2006)
Vicedo, J.L., Rodríguez, H., Peñas, A., Massot, M.: Los sistemas de Búsqueda de Respuestas desde una perspectiva actual. Revista de la Sociedad Española para el Procesamiento del Lenguaje Natural 31 (2003)
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Denicia-Carral, C., Montes-y-Gómez, M., Villaseñor-Pineda, L., Hernández, R.G. (2006). A Text Mining Approach for Definition Question Answering. In: Salakoski, T., Ginter, F., Pyysalo, S., Pahikkala, T. (eds) Advances in Natural Language Processing. FinTAL 2006. Lecture Notes in Computer Science(), vol 4139. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11816508_10
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DOI: https://doi.org/10.1007/11816508_10
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