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Emerging Cluster Analysis Of Sci Journals And Its Efficiency

Author

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  • YUNFENG CHANG

    (College of Science, China Three Gorges University, YiChang, HuBei 443002, China)

  • YUAN PING

    (Information Security Center, Beijing University of Posts and Telecommunications, Beijing 100876, China)

Abstract

Cluster analysis is an important way to ascertain whether or not a complex system consists of sub-clusters with different properties. On the basis of journal citation pattern, we clustered 1896 SCI journals in an emerging way (emerging clustering) in this paper. By this emerging clustering, the data to be checked for clustering is reduced from$O(N^{2}_{J})$toO(NJ)(NJis the total number of journals), this reduction could reduce the time complexity of clustering to a certain extent. During the clustering process, characteristic numbers of clusters are obtained, which correspond to various resolution scales for viewing the journals and might be helpful in understanding the mutual interactions among various knowledge domains. Its efficiency is further checked by comparisons between emerging clustering and hierarchical clustering with different inter-cluster linkage techniques. Statistical properties and comparisons of the clustering results show that this is an efficient clustering method for journal system. It could be a helpful improvement for traditional classification methods based on subjective analysis.

Suggested Citation

  • Yunfeng Chang & Yuan Ping, 2011. "Emerging Cluster Analysis Of Sci Journals And Its Efficiency," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 22(11), pages 1247-1256.
    • Handle: RePEc:wsi:ijmpcx:v:22:y:2011:i:11:n:s0129183111016865
    DOI: 10.1142/S0129183111016865
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