情报杂志2016，Vol.35Issue(9)：146-151,157,7.DOI:10.3969/j.issn.1002-1965.2016.09.026
区间分割概念格及其在作者共被引分析中的应用
The Interval Partition Concept Lattice and Its Application in Author Co-citation Analysis
摘要
Abstract
[ Purpose/Significance] The author co-citation analysis, viz ACA, is an important method to reveal the relationship between the author and the knowledge structure of the research domain. In order to enrich the research methods of ACA, the concept lattice is intro-duced into ACA in this paper. As the limitation of the concept lattice, the interval partition concept lattice is proposed. And the calculating formula of the research strength in ACA is given. [ Method/Process] Taking discipline service as the research subject, firstly, we select the core author, and extract five factor components of the core of the similarity matrix. Then the interval partition for six successive factor attribute values is cut apart respectively. Finally, we construct the interval partition concept lattice and intercept the author group of each factor attribute in ConExp-1. 3. Lastly, we give out the research strength of the research direction. [Result/Conclusion]Compared with the traditional clustering environment such as SPSS, Matlab and Ucinet6. 0, the interval partition concept lattice can not only find the core author of the research topics, but also find the leading figure in the research direction, and can obtain the research strength of the various research directions. The interval partition concept lattice can deal with the problem of multi valued attributes, clustering results are reliable, and the method can be applied to the clustering process of literature analysis, co-word analysis and periodical analysis.关键词
因子分析/区间分割/概念格/作者共被引分析/聚类分析Key words
factor analysis/interval partition/concept lattlce/author co-citation analysis/clustering analysis分类
社会科学引用本文复制引用
周奇志,李秀霞,程结晶..区间分割概念格及其在作者共被引分析中的应用[J].情报杂志,2016,35(9):146-151,157,7.基金项目
国家社会科学基金项目“文献内容分析与引文分析融合的知识挖掘与发现研究”(编号:16BTQ074)的阶段性成果之一。 （编号:16BTQ074）
