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A Text Mining Approach for Definition Question Answering

  • Claudia Denicia-Carral
  • Manuel Montes-y-Gómez
  • Luis Villaseñor-Pineda
  • René García Hernández
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4139)

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%.

Keywords

Pattern Mining Ranking Score Question Answering Pattern Discovery Definition Pattern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Claudia Denicia-Carral
    • 1
  • Manuel Montes-y-Gómez
    • 1
  • Luis Villaseñor-Pineda
    • 1
  • René García Hernández
    • 1
  1. 1.Language Technologies Group, Computer Science DepartmentNational Institute of Astrophysics, Optics and Electronics (INAOE)Mexico

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