한국문헌정보학회지 (Journal of the Korean Society for Library and Information Science)

한국문헌정보학회 (Korean Society For Library And Information Science)
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인용 지표를 이용한 재순위화 및 질의 확장의 성능 평가 - 인용색인 데이터베이스를 기반으로 -

Performance Evaluation of Re-ranking and Query Expansion for Citation Metrics: Based on Citation Index Databases

  • 이혜경 (경북대학교 문헌정보학과) ;
  • 이용구 (경북대학교 문헌정보학과)
  • 투고 : 2023.07.22
  • 심사 : 2023.08.12
  • 발행 : 2023.08.31
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초록

본 연구의 목적은 인용 지표가 인용 색인 데이터베이스의 검색성능 향상에 기여할 가능성을 파악하는 데에 있다. 이를 위하여 본 연구는 문헌정보학 분야 10개의 질의를 Web of Science에서 검색하여 수집한 3,467건의 문헌과 2000년부터 2021년까지 SSCI 문헌정보학 분야 저널 85종에 수록된 60,734건의 문헌을 기반으로 적합성 판단을 거쳐, 검색 결과의 상위 100순위에 대한 성능 및 검색 방식과 인용 지표를 활용한 재순위화, 그리고 벡터 공간모형 검색시스템 구축 등에 따른 질의 확장 실험을 수행하였다. 그 결과 첫째, 인용 지표를 단독으로 사용한 재순위화의 성능은 Web of Science의 검색성능과 상이하였으며, 인용 지표는 Web of Science 기존 시스템에 적용되지 않는 독립적인 지표로 작용하고 있었다. 둘째, 고유 질의어 수에 질의어의 총 출현 빈도를 조합하고 인용수를 보조적으로 사용했을 때, 성능에 긍정적인 영향을 미칠 것으로 확인하였다. 셋째, 질의 확장에서는 전반적으로 벡터 공간모형 기반 검색시스템의 기본 성능 대비 성능이 향상되었다. 넷째, 이용자 적합성을 통해 질의 확장을 적용한 경우가 시스템 적합성을 적용한 경우보다 성능이 향상 되었다. 다섯째, 피인용 수를 적합 문헌과 더불어 사용하면 최상위권 내 적합 문헌에서의 순위 변동 가능성을 보여주었다.

The purpose of this study is to explore the potential contribution of citation metrics to improving the search performance of citation index databases. To this end, the study generated ten queries in the field of library and information science and conducted experiments based on the relevance assessment using 3,467 documents retrieved from the Web of Science and 60,734 documents published in 85 SSCI journals in the field of library and information science from 2000 to 2021. The experiments included re-ranking of the top 100 search results using citation metrics and search methods, query expansion experiments using vector space model retrieval systems, and the construction of a citation-based re-ranking system. The results are as follows: 1) Re-ranking using citation metrics differed from Web of Science's performance, acting as independent metrics. 2) Combining query term frequencies and citation counts positively affected performance. 3) Query expansion generally improved performance compared to the vector space model baseline. 4) User-based query expansion outperformed system-based. 5) Combining citation counts with suitability documents affected ranking within top suitability documents.

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