정보과학회 컴퓨팅의 실제 논문지 (KIISE Transactions on Computing Practices)

  • 제23권11호
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  • Pages.611-616
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  • 2017
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  • 2383-6318(pISSN)
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  • 2383-6326(eISSN)
한국정보과학회 (Korean Institute of Information Scientists and Engineers)
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토픽 모델을 사용한 도메인 중심 질의 확장 기술

Domain Centered Query Expansion Technique using Topic Model

  • 이상훈 (에모리대학교 신경학과) ;
  • 문승진 (수원대학교 컴퓨터학과)
  • 투고 : 2016.06.02
  • 심사 : 2016.09.26
  • 발행 : 2017.11.15
⟨ 이전 논문 다음 논문 ⟩

초록

정보검색에서 질의확장은 가장 널리 알려진 기술로서 사용자가 입력한 질의에 외부적인 지식을 추가해서 조건에 맞게 질의를 확장시켜 검색도구의 능력을 향상시키는데 많이 사용되어 왔다. 하지만, 질의에 사용되는 단어의 애매모호함은 검색도구가 성능을 낮추기 때문에 이러한 문제는 여전히 풀어야 할 과제로 남아있다. 본 논문에서는 단어의 의미를 나타낼 수 있는 도메인을 사용해서 이러한 문제를 해결하는 방법을 제시한다. 특히 토픽 모델을 이용한 도메인 중심 모델을 사용해서 질의를 확장하는 기술을 제안한다. 실험은 기존 모델들과 비교로 이루어졌고, 그 결과 제시된 방법은 높은 성능을 보이는 것으로 나타났다.

In the area of Information Retrieval, Query Expansion is a well-known technique that uses external knowledge to increase an inquiry generated by users. However, ambiguous words used in the query decrease the performance of search tools. In this paper, we propose a solution to the above problem, by using domain knowledge which identifies the meaning of words in the query. In particular, we present a domain centered query expansion technique that magnifies a query using domains. By comparing with various query expansion models, we demonstrate that the proposed model performs better than the other models.

키워드

참고문헌

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