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Assessing the Impact of Thesaurus-Based Expansion Techniques in QA-Centric IR

  • Luís Sarmento
  • Jorge Teixeira
  • Eugénio Oliveira
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5706)

Abstract

We study the impact of using thesaurus-based query expansion methods at the Information Retrieval (IR) stage of a Question Answering (QA) system. We focus on expanding queries for questions regarding actions and events, where verbs have a central role. Two different thesaurus are used: the OpenOffice thesaurus and an automatically generated verb thesaurus. The performance of thesaurus-based methods is compared against what is obtained by (i) executing no expansion and (ii) applying a simple query generalization method. Results show that thesaurus-based approaches help improving recall at retrieval, while keeping satisfactory precision. However, we confirm that positive impact for the final QA performance is mostly achieved due to increase in recall, which can also be obtained by using simpler methods. Nevertheless, because of its better relative precision thesaurus-based expansion is effective in selectively reducing the number of irrelevant text passages retrieved, thus reducing computational load in the answer extraction stage.

Keywords

Query Expansion Question Answering Statistical Machine Translation Text Passage 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 2009

Authors and Affiliations

  • Luís Sarmento
    • 1
  • Jorge Teixeira
    • 1
  • Eugénio Oliveira
    • 1
  1. 1.Laboratorio de Inteligência Artificial e Ciências de ComputadoresFaculdade de Engenharia da Universidade do PortoPortoPortugal

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