Research on Fine-grained Semantic Co-word Analysis Method

  • Wang Yulin ,
  • Wang Zhongyi
Expand
  • 1. Center for Studies of Information Resources, Wuhan University, Wuhan 430072;
    2. School of Information Management, Central China Normal University, Wuhan 430079

Received date: 2014-08-28

  Revised date: 2014-10-10

  Online published: 2014-11-07

Abstract

In view of the problems in co-word analysis method such as the different quality with the same quantity and the difference of result explanation, this paper proposes a fine-grained semantic co-word analysis method. In order to realize the fine-grained semantic co-word analysis, on one hand, the statistic unit of the co-words is segmented from "articles unit" to "knowledge (RDF) unit"; on the other hand, the co-word analysis method is semanticized and the co-word semantic information is integrated into the analyzing process. At last, this paper verifies the scientificity and effectiveness of the proposed method through experiment.

Cite this article

Wang Yulin , Wang Zhongyi . Research on Fine-grained Semantic Co-word Analysis Method[J]. Library and Information Service, 2014 , 58(21) : 73 -80 . DOI: 10.13266/j.issn.0252-3116.2014.21.011

References

[1] Callon M, Courtial J P, Turner W A,et al. From translations to problematic Net-works: An introduction to co-word analysis[J]. Social Science Information,1983,22(2) : 191-235.

[2] Coulter N, Monarch I, Konda S. Software engineering as seen through its research literature: A study in co-word analysis[J]. Journal of the American Society for Information Science, 1998, 49(13):1206-1223.

[3] Rokaya M,Elsayed A, Masao F, et al. Ranking of field association terms using co-word analysis[J]. Information Processing and Management,2008,44(2): 738-755.

[4] López-Herrera A G, Cobo M J, Herrera-Viedma E, et al. A bibliometric study about the research based on hybridating the fuzzy logic field and the other computational intelligent techniques: A visual approach[J]. International Journal of Hybrid Intelligent Systems, 2010, 7(1): 17-32.

[5] He Qin. Knowledge discovery through co-word analysis[J]. Library Trends, 1999,48(1):133-159.

[6] Law J, Whittaker J. Mapping acidification research: A test of the co-word method[J]. Scientometrics, 1992,23(3):417-461.

[7] Wang Zhengyi, Li Gang, Li Chunya, et al. Research on the semantic-based co-word analysis[J]. Scientometrics, 2012, 90(3): 855-875.

[8] Peters H P F, van Raan A F J. Co-word-based science maps of chemical engineering. Part I: Representations by direct multidimensional scaling[J]. Research Policy, 1993, 22(1): 23-45.

[9] Bizer C, Heath T, Berners-Lee T. Linked data-The story so far[J]. International Journal on Semantic Web and Information Systems, 2009, 5(3): 1-22.

[10] Sderbck A, Malmsten M. LIBRIS-linked library data[J]. Nodalities,2008(5):19-20.

[11] Bermeta D, Phipps J. Best practice recipes for publishing RDF vocabularies W3C working draft[EB/OL].[2014-08-27]. http://www.w3.org/TR/swbp-voca-pub/.

[12] Hu Yingjie, Janowicz K, McKenzie G, et al. A linked-data-driven and semantically-enabled journal portal for scientometrics[C]//The Semantic Web-ISWC 2013. Berlin Heidelberg:Springer, 2013: 114-129.

[13] Glenisson P, Glänzel W, Persson O. Combining full-text analysis and bibliometric indicators. A pilot study[J]. Scientometrics, 2005, 63(1): 163-180.

[14] Callon M, Courtial J P, Laville F, et al. Co-word analysis for basic and technological re-search[J]. Scientmetrics,1991,22(2):155-205.

[15] 钟伟金,李佳. 共词分析法研究(一)——共词分析的过程和方式[J]. 情报杂志,2008(5):70-72.

Outlines

/