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基于RDA的标签与书目数据关联方法初探

  • 魏来 ,
  • 王雯霞
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  • 1. 东北师范大学计算机科学与信息技术学院;
    2. 中国科学技术信息研究所
魏来,东北师范大学计算机科学与信息技术学院副教授,中国科学技术信息研究所博士后,E-mail:weil875@nenu.edu.cn;王雯霞,东北师范大学计算机科学与信息技术学院硕士研究生。

收稿日期: 2013-12-16

  修回日期: 2014-02-16

  网络出版日期: 2014-03-05

基金资助

本文系国家自然科学基金项目“基于海量数字资源的科研关系网络构建研究”(项目编号:71203208)和教育部人文社会科学基金青年项目“基于语义化标注的网络学习资源组织方法及实证研究”(项目编号:11YJCZH180)研究成果之一。

The Research on Association Method between Tags and Bibliographic Data Based on RDA

  • Wei Lai ,
  • Wang Wenxia
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  • 1. School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117;
    2. Institute of Scientific and Technical Information of China, Beijing 100038

Received date: 2013-12-16

  Revised date: 2014-02-16

  Online published: 2014-03-05

摘要

通过研究标签属性与书目实体属性之间的各种映射关系,实现标签数据与书目数据之间的有效关联,提出基于RDA的标签与书目数据有效关联的方法,建立标签属性与书目数据属性之间的有效映射,以更好地实现资源之间的链接,促进资源发现与共享。

本文引用格式

魏来 , 王雯霞 . 基于RDA的标签与书目数据关联方法初探[J]. 图书情报工作, 2014 , 58(05) : 69 -74 . DOI: 10.13266/j.issn.0252-3116.2014.05.012

Abstract

The paper analyzed various relationships between the tagging attributes and bibliographic entity attributes, in order to achieve the effective association between the tagging data and bibliographic data. The paper proposed the association method between tagging data and bibliographic data based on RDA, established effective mapping method between the tagging attributes and bibliographic entity attributes, to realize effectively resource link and promote resource discovery and sharing.

参考文献

[1] Miranda G, Andreas H, Gerd S, et al. Conceptual clustering of social bookmarking sites [EB/OL].[2013-12-10]. http://i-know.tugraz.at/wp-content/uploads/2008/11/43_conceptual-clustering-of-social-bookmarking-sites.pdf.
[2] Daniel R, Paul H, Christopher D, et al.Clustering the Tagged Web[C]//WSDM'09 Proceedings of the Second ACM International Conference on Web Search and Data Mining.NewYork:ACM,2009:54-63.
[3] Eric T, Wang W M, Cheung C F, et al.A concept-relationship acquisition and inference approach for hierarchical taxonomy construction from tags[J]. Information Processing & Management, 2010(1): 44-57.
[4] Lux M, Dsinger G. From folksonomies to ontologies: Employing wisdom of the crowds to serve learning purposes[J]. International Journal of Knowledge and Learning(IJKL),2007(3):515-528.
[5] Maria.G. Harnessing Wikipedia for Smart Tags Clustering. [EB/OL].[2013-12-10]. http://wwwnew.ispras.ru/en/modis/downloads/grineva02.pdf.
[6] Chen Miao, Liu Xiaozhong, Qin Jian et al. Semantic relation extraction from socially-generated tags:A methodology for metadata generation[C]//Proceedings of the 2008 International Conference on Dublin Core and Metadata Applications.Berlin:Dublin Core Metadata Initiative,2008: 117-127.
[7] Spiteril F. The use of folksonomies in public library catalogues[J].Serials Librarian,2006(2):75-87.
[8] 贾君枝,李婷.分众分类与书目记录结合研究[J].情报理论与实践,2011,34(7):38-43.
[9] Thomas M, Caudle D M, Schmitz C M. To tag or not to tag?[J].Library Hi-Tech, 2009(3):411-434.
[10] 冯亚惠.AACR 的替代品——资源描述与检索(RDA)介绍[J].图书情报工作,2007,51(1):129-131.
[11] 刘炜,胡小菁, 钱国富, 等.RDA与关联数据[J].中国图书馆学报,2012(1):34-42.
[12] 刘素清.IFLA书目记录功能需求(FRBR)初探[J].大学图书馆学报,2004(6):65-69.
[13] 吴芬.国外标签本体研究进展[J].现代情报,2009(11):16-20.
[14] 熊回香,廖作芳,蔡青.典型标签本体模型的比较分析研究[J].情报学报,2011(5):479-486.
[15] Joint Steering Committee for Development of RDA:RDA[EB/OL]. [2013-12-10].http://www.rda-jsc.org/rda.html.

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