Demonstration of the importance of system ingredients with strong similarity in cluster analysis

Author

Chang, YunFeng ; Zhao, Yuan ; Feng, ShengQin

Author_Institution

Coll. of Sci., China Three Gorges Univ., Yichang, China

fYear

2011

fDate

8-10 Aug. 2011

Firstpage

309

Lastpage

312

Abstract

In this paper, we propose one method to demonstrate the importance and effectiveness of system ingredients with strong similarity in cluster analysis. As a test, we clustered 1578 SSCI journals with three different collections of journal-journal similarities, which are computed from the aggregated journal-journal citation reports of the Institute of Scientific Information (ISI). The statistical properties of the clustering results and the consistency of the results with ISI category demonstrate the importance and efficiency of those predominant system ingredients with strong similariy, and may aid the management of information for increasingly large complex systems analysis.

Keywords

citation analysis; electronic publishing; information retrieval; pattern clustering; statistical analysis; SSCI journals; aggregated journal-journal citation reports; cluster analysis; complex systems analysis; information management; journal-journal similarities; statistical properties; system ingredients; Clustering methods; Complex networks; Complexity theory; Educational institutions; Measurement; Physics; Probability distribution; cluster analysis; predominant; similarity;

fLanguage

English

Publisher

ieee

Conference_Titel

Emergency Management and Management Sciences (ICEMMS), 2011 2nd IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-9665-5

Type

conf

DOI

10.1109/ICEMMS.2011.6015683

Filename

6015683