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Author Disambiguation Using Co-Author Network and Supervised Learning Approach in Scholarly Data

첫 페이지 보기
  • 발행기관
    보안공학연구지원센터(IJSEIA) 바로가기
  • 간행물
    International Journal of Software Engineering and Its Applications SCOPUS 바로가기
  • 통권
    Vol.10 No.4 (2016.04)바로가기
  • 페이지
    pp.73-82
  • 저자
    Jae-Wook Seol, Seok-Hyoung Lee, Kwang-Young Kim
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A273101

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원문정보

초록

영어
When using search engine services to search for scholarly articles, obtaining quick and accurate search results from a huge set of scholarly information is always important. However, most of the domestic and foreign search engine services for scholarly articles present a broad range of the results that correspond to the query of the researcher’s name. Such results contribute in lowering the search precision and require users to spend time and effort to verify the results and find the necessary information. Such a problem is called “author ambiguity”, while solving this problem is called “author disambiguation.” An author disambiguation method classifies the authors with the same name into an actual person. By resolving author ambiguity, better search results can be obtained; this increases the recall rate and accuracy when searching for scholarly articles. In order to resolve author ambiguity in this paper, we shall expand the co-author network and identify the author using the co-author network information and basic bibliographic information as the features for machine learning Support Vector Machine. To examine the effectiveness of the proposed method, we test the author disambiguation method by targeting 92,100 IT-related scholarly data generated in Korea. Author disambiguation results through the expansion of co-author network are shown to have an F-1 measure of 94.79%. The result confirms that the author disambiguation method through the implementation of the co-author network is effective.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Author Disambiguation using Co-author Network
  3.1. Generating Same Name Group
  3.2 Expanding Co-author Network
  3.3 Generating Features for Author Disambiguation and Performance
  3.4 Classifying Author Disambiguation Using Support Vector Machine
 4. Experiments
  4.1. Data Set
  4.2. Experimental Results and Analysis
 5. Discussion
 6. Conclusion
 References

키워드

Author disambiguation Co-author network Support Vector Machine Classification

저자

  • Jae-Wook Seol [ KISTI(Korea Institute of Science and Technology Information) ]
  • Seok-Hyoung Lee [ KISTI(Korea Institute of Science and Technology Information) ] Corresponding Author
  • Kwang-Young Kim [ KISTI(Korea Institute of Science and Technology Information) ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    보안공학연구지원센터(IJSEIA) [Science & Engineering Research Support Center, Republic of Korea(IJSEIA)]
  • 설립연도
    2006
  • 분야
    공학>컴퓨터학
  • 소개
    1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업

간행물

  • 간행물명
    International Journal of Software Engineering and Its Applications
  • 간기
    월간
  • pISSN
    1738-9984
  • 수록기간
    2008~2016
  • 등재여부
    SCOPUS
  • 십진분류
    KDC 505 DDC 605

이 권호 내 다른 논문 / International Journal of Software Engineering and Its Applications Vol.10 No.4

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