• Journal of the Korean Society for Library and Information Science
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• v.51 no.4
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• pp.35-52
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• 2017

This paper aims to explore the citation patterns of conference papers in 'Information Science' discipline and to analze impacts of various cited works-related factors on future citations of conference papers. Existing bibliometric studies has investigated citation patterns and the statistical relations between a variety of bibliographic factors and the future citations of literature. However, the attentions have been focused largely on journal articles, and the bibliometric studies targeting conference papers are still in an infant stage. Therefore, this study, which is based on 1,904 conference papers in 'Information Science' field, examined several citation patterns and the contributions of the factors about cited works - the number of cited works, type of cited works, citation rates and ages of cited works at the time of being cited and the rate of self-citedness - to the future citation of the citing target articles. The data source of this study including the properties of target articles and cited works and citation rates of target articles was Scopus. As the results, 53% and 29% of the cited works were conference papers and journal articles, respectively. 14% of them are non-traditional types such as web pages, technical reports, patent, etc. More than 60% of the cited works were 5 years old or less. Among several factors considered in this paper, the number of conference papers and the number of non-traditional types of works are the most contributing factors on the citation rates of target articles. The recency of the cited works is also significant contributor on the citation rates of target articles. That is, the target articles citing more conference papers and non-traditonal types of works earned more citations. The target articles citing recent works also earned more citations.

• Journal of Korean Library and Information Science Society
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• v.39 no.4
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• pp.377-395
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• 2008

This article aims to help decide until when a library has to hold journal volumes for user efficiency by measuring the value of academic journals to find the frequency of journal use over the elapsed time based on the half-life index-number of literature obsolescence by Burton & Kebler. Four general subjects categories in science was analyzed. (4 detailed subjects in mathematics, 12 in physics, 12 in chemistry, 14 in technology was selected.) As a result, citation ages are $20{\sim}29$ years in mathematics, $8{\sim}11$ in physics, chemistry, and technology. Average half-life indexes are 11.22 year in mathematics, 7.5 in physics, 8.4 in chemistry, and 8.88 in technology.

• Journal of the Korean Society for Library and Information Science
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• v.47 no.1
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• pp.15-37
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• 2013

The purpose of this study is to develop a faceted classification that enables the conceptualization and the organization of Korean food information. 23,470 terms were collected, categorized, and analyzed from the table of contents in 776 monographs and directory headings in portal sites related to Korean food. In order to develop the Korean food classification, common properties were analyzed in the process of categorizing terms. Then basic facets and subfacets were defined and assigned, and hierarchies among facets and concepts, citation orders, and notations were decided. As a result, the classification scheme consisted of 16 basic facets and 85 subfacets. The citation order of facets was proposed in order of Personality facet (kinds of dishes), Matter facet (materials, cooking utensils/equipment/containers, and nutrients), Energy facet (cooking processes and techniques, eating sense, type of cooking, table services, and agents of cooking), Space facet (countries/ethnic groups/geography, and eating places), Time facet (situation/purposes, season, time of meals, periods, and ages). The result of this study will be used for organizing, searching, retrieving, and providing Korean food information effectively around the world. Also, it will provide a foundation for developing subject-oriented classification using facet analysis in other disciplines.