Library and Information Science

Library and Information Science ISSN: 2435-8495
三田図書館・情報学会 Mita Society for Library and Information Science
〒108‒8345 東京都港区三田2‒15‒45 慶應義塾大学文学部図書館・情報学専攻内 c/o Keio University, 2-15-45 Mita, Minato-ku, Tokyo 108-8345, Japan
Library and Information Science 61: 119-151 (2009)

原著論文Original Article

FRBR OPAC構築に向けた著作の機械的同定法の検証JAPAN/MARC書誌レコードによる実験Automatic identification of “Works” toward construction of FRBRized OPACs: An experiment on JAPAN/MARC bibliographic records

筑波大学大学院図書館情報メディア研究科Graduate School of Library, Information and Media Studies, University of Tsukuba ◇ 〒305-8550 茨城県つくば市春日一丁目2番地 ◇ Kasuga 1-2, Tsukuba, Ibaraki 305-8550, Japan

受付日:2008年11月27日Received: November 27, 2008
受理日:2009年4月4日Accepted: April 4, 2009
発行日:2009年6月30日Published: June 30, 2009




Purpose: Efforts have been made to improve the OPACs by collocating bibliographic records sharing the same “work” and navigating users among records under a certain “work,” according to the Functional Requirements for Bibliographic Records (FRBR). This paper investigates methods of automatically identifying “works,” i.e., grouping bibliographic records sharing the same work, for the JAPAN/MARC records, which are typical Japanese bibliographic records created and maintained by libraries in Japan. It reports the extent to which records can be automatically identified as members of a particular work and also which of the possible methods are effective.

Methods: The method used in this study is to generate work identification keys for each work represented in a bibliographic record and then to bring the keys representing the same works together. The keys are in principle constructed as a combination of an author name and a title from the record. Several methods of generating such keys were examined and the clustering of keys was executed for each method. The clusters built automatically were evaluated by comparing them with the sample correct sets built manually.

Results: The results of the experiment show that the proposed method is effective in average cases; however, the performance depends on the characteristics of works, for example, the volume of records sharing the same work, whether anonymous or not, and whether uniform titles exist. It also shows that it is effective to generate keys for every bibliographic hierarchical level with data elements such as author headings, statements of responsibility, descriptive titles, and title headings.

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