The Journal of Society for e-Business Studies (한국전자거래학회지)

Society for e-Business Studies (한국전자거래학회)
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Academic Conference Categorization According to Subjects Using Topical Information Extraction from Conference Websites

학회 웹사이트의 토픽 정보추출을 이용한 주제에 따른 학회 자동분류 기법

  • Lee, Sue Kyoung (Department of Industrial and Management Engineering, Incheon National University) ;
  • Kim, Kwanho (Department of Industrial and Management Engineering, Incheon National University)
  • Received : 2017.03.17
  • Accepted : 2017.05.19
  • Published : 2017.05.31
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Abstract

Recently, the number of academic conference information on the Internet has rapidly increased, the automatic classification of academic conference information according to research subjects enables researchers to find the related academic conference efficiently. Information provided by most conference listing services is limited to title, date, location, and website URL. However, among these features, the only feature containing topical words is title, which causes information insufficiency problem. Therefore, we propose methods that aim to resolve information insufficiency problem by utilizing web contents. Specifically, the proposed methods the extract main contents from a HTML document collected by using a website URL. Based on the similarity between the title of a conference and its main contents, the topical keywords are selected to enforce the important keywords among the main contents. The experiment results conducted by using a real-world dataset showed that the use of additional information extracted from the conference websites is successful in improving the conference classification performances. We plan to further improve the accuracy of conference classification by considering the structure of websites.

최근 온라인상에 게시된 학회정보가 급증함으로써 주제에 따른 학회정보의 자동분류는 연구자들에게 효율적인 관련 학회 탐색을 가능하게 한다. 그러나 대부분의 학회 목록 제공 서비스에서는 학회명칭, 날짜, 위치, URL 등의 정보만 제공하기 때문에 학회 주제를 파악할 수 있는 정보는 학회명칭에 국한된다. 따라서 본 연구에서는 URL을 통한 학회 웹사이트의 토픽정보를 추출함으로써 학회정보량의 부족문제를 해결하고, 동시에 양질의 정보로 학습의 성능을 향상시키는 기법을 제안한다. 구체적으로는 웹사이트 URL을 통해 수집한 HTML 문서로부터 주요 콘텐츠를 추출하고, 학회명칭과 유사한 토픽 키워드 정보를 선정하여 추가 가중치를 부여한다. 실 데이터를 활용한 실험 결과, 제안된 방법인 추가적인 웹 콘텐츠 정보의 사용은 주제에 따른 학회 분류의 성능을 성공적으로 향상시킬 수 있음을 확인하였다. 추후 연구에서는 웹 사이트의 구조를 고려한 토픽 정보추출을 통해 분류의 정확성을 더욱 향상시킬 계획이다.

Keywords

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