바로가기메뉴

본문 바로가기 주메뉴 바로가기

Journal of Korean Library and Information Science Society

  • P-ISSN2466-2542
  • KCI

Article Contents

Prev Next
e-Submission

Vol.42 No.1

Citation Share

Analysis and Evaluation of Most Clicked Documents of Korean Search Portal

Journal of Korean Library and Information Science Society / Journal of Korean Library and Information Science Society, (P)2466-2542;
2011, v.42 no.1, pp.325-338
https://doi.org/10.16981/kliss.42.1.201103.325

(2011). Analysis and Evaluation of Most Clicked Documents of Korean Search Portal. Journal of Korean Library and Information Science Society, 42(1), 325-338, https://doi.org/10.16981/kliss.42.1.201103.325

Abstract

This study aims to investigate characteristics of most clicked documents of Naver's universal search service. In particular, this study analyzed characteristics of most clicked documents such as click ratio, collection distribution, and yearly distribution. Also, clicked documents were evaluated in terms of relevance, credibility, and currency. In conducting this study, query logs and click logs of unified search service were analyzed. The results of this study show that most clicks occurred in blog collection and average click concentration rate reached almost 50%. Also, the relevance and currency of most clicked documents were quite high, but credibility of these documents were on average level. The results of this study can be implemented to the portal's effective development of searching algorithm and interface.

keywords
Web Searching, Most Clicked Documents, Search Portals, Log Analysis, Web Searching, Most Clicked Documents, Search Portals, Log Analysis, 웹 검색, 클릭 집중 문서, 검색 포털, 로그 분석

Reference

1.

1) 유태명, 김준태, “링크 빈도와 클릭 빈도를 이용하는 메타 검색엔진의 설계,” 한국정보과학회 봄 학술발표논문집, 제27권, 제1호(2000), pp.292-294.

2.

2) S. Park, and J. Lee, “Unified search service of NAVER, a major Korean search engine,” In: the 31st SIGIR annual international ACM SIGIR Workshop on Aggregated Search, edited by M. Lalmas, and V. Murdock, Singapore, 2008, pp.17-19.

3.

3) T. Joachims, “In optimizing search engines using clickthrough data,” In: The 8th ACM SIGKDD international conference on Knowledge Discovery and Data Mining, edited by D. Hand, D. Keim, and R. Ng, Edmonton, Alberta, Canada, 2002, pp.133-142.

4.

4) T. Joachims et al., “Accurately interpreting clickthrough data as implicit feedback,” In: the 28th annual international ACM SIGIR conference on Research and development in information retrieval, edited by R. A. Baeza-Yates, N. Ziviani, G. Marchionini, Moffat, Al, and J. Tait, Salvador, Brazil, 2005, pp.154-161.

5.

5) T. Joachims et al., “Evaluating the accuracy of implicit feedback from clicks and query reformulations in Web search,” ACM Transactions of Information Systems, Vol.25, No.2(2007), doi: <http://doi.acm.org/10.1145/1229719.1229181>.

6.

6) S. Jung, J. L. Herlocker, J. L, and J. Webster, “Click data as implicit relevance feedback in web search,” Information Processing and Management, Vol.43, No.3(2007), pp.791-807.

7.

7) B. J. Jansen, and A. Spink, “An analysis of Web searching by European AlltheWeb.com users,” Information Processing and Management, Vol.41, No.2(2004), pp.361-381.

8.

8) B. J. Jansen, and A. Spink, “How are we searching the World Wide Web?: An analysis of nine search engine transaction logs,” Information Processing and Management, Vol.42, No.1(2005), pp.248-263.

9.

9) A. Spink, D. Wolfram, and B. J. Jansen, “Searching the Web: The public and their queries,” Journal of the American Society for Information Science and Technology, Vol.52, No.3(2001), pp.226-234.

10.

10) D. Tjondronegoro, A. Spink, and B. J. Jansen, “A study and comparison of multimedia Web searching: 1997-2006,” Journal of the American Society for Information Science and Technology, Vol.60, No.9(2009), pp.1756-1768.

11.

11) 박소연, 이준호, 김지승, “클릭 로그에 근거한 네이버 검색 질의의 형태 및 주제 분석,” 한국문헌정보학회지, 제39권, 제1호(2005. 6), pp.265-278.

12.

12) 박소연, “국내 포털 이용자들의 멀티미디어 검색 행태 분석,” 한국문헌정보학회지, 제44권, 제1호(2010. 3), pp.101-115.

13.

NHN Home page, <http://www.nhncorp.com/nhn/service/naver.nhn>.

14.

14) H. Arkin, and R. Colton, Tables for Statisticians(New York : Barnes & Noble Inc., 1963).

15.

16) 노정순, “Invisible Web 탐색도구의 성능 비교 및 분석,” 정보관리학회지, 제21권, 제3호(2004. 9), pp.203-225.

16.

17) 맹성현 등, “정보 검색 시스템 평가를 위한 균형 테스트 컬렉션 구축,” 정보관리학회지, 제16권, 제2호(1999. 6), pp.135-148.

17.

18) 박소연, 이준호, “주요 검색 포탈들의 통합 검색 서비스 비교 평가,” 한국도서관․정보학회지, 제39권, 제1호(2008. 3), pp.265-278.

18.

19) 박소연, 이준호, 전지운, “지식 검색 서비스 개선을 위한 문서의 적합도 및 신뢰도 분석,” 한국문헌정보학회지, 제40권, 제2호(2006. 6), pp.299-314.

Journal of Korean Library and Information Science Society

e-Submission OA Policy