Community Discovery Algorithm of Citation Semantic Link Network

Citation semantic link network make the citation network to not only has the ability of semantic representation but also has the ability of semantic reasoning by combining semantic link network with citation network. It provides a more efficient method for the citation network retrieval and the complex network research. Based on citation semantic link network, this paper proposes a community discovery algorithm of citation semantic link network. This algorithm can find the semantic community in citation semantic link network. Revealing the community structure of citation semantic link network not only is of great significance for understanding the citation semantic link network structure and analyzing the network characteristics, but also has great meaning for understanding the cutting-edge issues of this field, and predicting the future development direction of this field and possible research hotspots.

[1]  Per O. Seglen,et al.  The Skewness of Science , 1992, J. Am. Soc. Inf. Sci..

[2]  Yuhui Qiu,et al.  Schema Reasoning and Semantic Representation for Citation Semantic Link Network , 2009, 2009 Third International Symposium on Intelligent Information Technology Application.

[3]  Xiang Li,et al.  Peer-to-Peer in Metric Space and Semantic Space , 2007, IEEE Transactions on Knowledge and Data Engineering.

[4]  Alexander P. Pons Object prefetching using semantic links , 2006, DATB.

[5]  Hai Zhuge,et al.  Communities and Emerging Semantics in Semantic Link Network: Discovery and Learning , 2009, IEEE Transactions on Knowledge and Data Engineering.

[6]  Hai Zhuge,et al.  Active e-document framework ADF: model and tool , 2003, Inf. Manag..

[7]  Hai Zhuge,et al.  Schema Theory for Semantic Link Network , 2008, 2008 Fourth International Conference on Semantics, Knowledge and Grid.

[8]  Gang Wang,et al.  Research on similarity calculation of citation semantic link network , 2012, 2012 IEEE International Conference on Computer Science and Automation Engineering.

[9]  Hai Zhuge,et al.  Retrieve images by understanding semantic links and clustering image fragments , 2004, J. Syst. Softw..

[10]  S. Redner How popular is your paper? An empirical study of the citation distribution , 1998, cond-mat/9804163.

[11]  D. Sornette,et al.  Stretched exponential distributions in nature and economy: “fat tails” with characteristic scales , 1998, cond-mat/9801293.