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Journal of the Korean Society for Library and Information Science

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Vol.38 No.1
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The Effectiveness of Hierarchic Clustering on Query Results in OPAC

Journal of the Korean Society for Library and Information Science / Journal of the Korean Society for Library and Information Science, (P)1225-598X; (E)2982-6292
2004, v.38 no.1, pp.35-50

(2004). The Effectiveness of Hierarchic Clustering on Query Results in OPAC. Journal of the Korean Society for Library and Information Science, 38(1), 35-50.
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Abstract

This study evaluated the applicability of the static hierarchic clustering model to clustering query results in OPAC. Two clustering methods(Between Average Linkage(BAL) and Complete Linkage(CL)) and two similarity coefficients(Dice and Jaccard) were tested on the query results retrieved from 16 title-based keyword searchings. The precision of optimal clusters was improved more than 100% compared with title-word searching. There was no difference between similarity coefficients but clustering methods in optimal cluster effectiveness. CL method is better in precision ratio but BAL is better in recall ratio at the optimal top-level and bottom-level clusters. However the differences are not significant except higher recall ratio of BAL at the top-level cluster. Small number of clusters and long chain of hierarchy for optimal cluster resulted from BAL could not be desirable and efficient.

keywords
OPAC, Document Clustering, Query Result, Similarity, Hierarchic Clustering, OPAC, Document Clustering, Query Result, Similarity, Hierarchic Clustering, 온라인 목록, 문헌 클러스터링, 계층 클러스터링, 탐색결과, 유사도

Reference

1.

노정순, (2004) OPAC에서 자동분류 열람을 위한 계층 클러스터링 연구, 정보관리학회지

2.

Carlyle, Allyson , (1996) Ordering author and work records: an evaluation of collection in online catalog displa,

3.

Croft, (1980189-195) “A Model of clustersearching based on classification,

4.

(1985) “Automatic classificationof book material repre-sented by back-of-book index ”Journal of Documentation,

5.

Griffiths, (1984) ”Journal of Documentation,

6.

Hearst, M, (1996) Reexamining the cluster hypothesis: Scatter/Gather on retrieval resul,

7.

Larson, (1986) University of California,

8.

(1991197-215) “The Decline of subjectsearching long-term trends andpatterns of index use in an onlinecatalog ”Journal of the AmericanSociety for Information Science,

9.

Leouski, A, (1998) Evaluating a visual navigation system for a digital library,

10.

Lynch, (19891989) Proceedings of a JointMeeting of the British Library,

11.

Peter, (1991) “Controlledand uncontrolled vocabularysubject searching in an academiclibrary online catalog,

12.

Preece, (1973189-190) “Clustering as an outputoption ”Proceedings of the AmericanSociety for information Science,

13.

Roussinov, D, (2001) Information navigation on the web by clustering and summarizing query results,

14.

Salton, (1971) The SMART RetrievalSystem-Experiments in AutomaticDocument Retrieval, Prentice-Hall

15.

Silverstein, D, (1997) Almost-constant-time clustering of arbitary corpus subsets,

16.

Tombros, A, (2002) The Effectiveness of query-specific hierarchic clustering in information retrieval,

17.

Vivisimo,

18.

Wibereley, S. E, (1995) User persistence in displaying online catalog posting: LUIS,

19.

Willett, (1985) ”Internation Forum on Informationand Documentation,

20.

Zamir, O, (1998) Web document clustering: A feasibility demonstration,

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