Journal of KIISE:Software and Applications (한국정보과학회논문지:소프트웨어및응용)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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A Term Weight Mensuration based on Popularity for Search Query Expansion

검색 질의 확장을 위한 인기도 기반 단어 가중치 측정

  • 이정훈 (동국대학교 컴퓨터공학과) ;
  • 전서현 (동국대학교 컴퓨터공학과)
  • Received : 2010.02.17
  • Accepted : 2010.06.05
  • Published : 2010.08.15
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Abstract

With the use of the Internet pervasive in everyday life, people are now able to retrieve a lot of information through the web. However, exponential growth in the quantity of information on the web has brought limits to online search engines in their search performance by showing piles and piles of unwanted information. With so much unwanted information, web users nowadays need more time and efforts than in the past to search for needed information. This paper suggests a method of using query expansion in order to quickly bring wanted information to web users. Popularity based Term Weight Mensuration better performance than the TF-IDF and Simple Popularity Term Weight Mensuration to experiments without changes of search subject. When a subject changed during search, Popularity based Term Weight Mensuration's performance change is smaller than others.

인터넷의 활용이 보편화 됨에 따라 사람들이 많은 정보를 웹을 통해 접할 수 있게 되었다. 정보의 양이 급격히 늘어나면서 검색 엔진은 사용자가 필요로 하지 않는 정보까지 보여주는 검색 성능의 한계를 가져왔다. 따라서 사용자는 원하는 정보를 검색하기 위해 과거보다 더 많은 시간과 노력이 필요하게 되었다. 이 연구에서는 질의 확장을 이용하여 사용자가 필요로 하는 정확한 정보를 신속하게 찾아서 제공할 수 있는 방법을 제안한다. 제안된 단어 가중치 평가방법은 검색 주제의 변동 없이 하나의 검색 주제를 검색할 경우 TF-IDF 또는 단순 인기도 측정법 보다 우수한 성능을 보인다. 또한 검색 중 주제를 변경하였을 때에도 검색 주제 변경 전과 유사한 성능으로 기존의 측정법 보다 빠르게 새로운 주제와 관련된 단어를 추출하고 정확한 가중치를 측정한다.

Keywords

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