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Query Expansion for Contextual Question Using Genetic Algorithms

  • Yasutomo Kimura
  • Kenji Araki
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4182)

Abstract

We propose a query expansion method using Genetic Algorithms(GA) in Japanese. Recently, question answering research focuses on contextual questions. Therefore a question answering system has to resolve contextual problems by using both previous questions and previous answers. This problem is largely related to query expansion because of the need to find new keywords. In the contextual processing, a query needs to find other suitable keywords from related resources. Although it is easy for a system to find related words, it is difficult to find a suitable combination of keywords. GA is better suited for a combination problem just like a knapsack problem. Therefore we apply GA to our contextual query expansion method. In the evaluation experiment, MRR was 0.2531 in 360 contextual questions. We confirm the MRR of our method is higher than that of the baseline. We illustrate our method and the experiment.

Keywords

Knapsack Problem Query Expansion Question Answering Anaphora Resolution Question Answering System 
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

  • Yasutomo Kimura
    • 1
  • Kenji Araki
    • 2
  1. 1.Otaru University of CommerceOtaruJapan
  2. 2.Graduate School of Information Science and TechnologyHokkaido UniversitySapporo-shiJapan

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