Structured use of external knowledge for event-based open domain question answering

ABSTRACT

One of the major problems in question answering (QA) is that the queries are either too brief or often do not contain most relevant terms in the target corpus. In order to overcome this problem, our earlier work integrates external knowledge extracted from the Web and WordNet to perform Event-based QA on the TREC-11 task. This paper extends our approach to perform event-based QA by uncovering the structure within the external knowledge. The knowledge structure loosely models different facets of QA events, and is used in conjunction with successive constraint relaxation algorithm to achieve effective QA. Our results obtained on TREC-11 QA corpus indicate that the new approach is more effective and able to attain a confidence-weighted score of above 80%.

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.7 Natural Language Processing
          Subjects: Language parsing and understanding

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.7 Natural Language Processing
          Subjects: Text analysis

General Terms:
Algorithms, Design, Experimentation, Performance

Keywords:
event-based QA, query formulation, question answering