Abstract
In this paper we present a new method to create small world networks based on K-means clustering analysis. Because of the close relationship between the small world networks and the data with clustering characteristics, the resulting networks based on K-means method have many properties of small world networks including small average distance, right skewed degree distribution, and the clustering effect. Moreover the constructing process also has shown some behaviors including networks formation and evolution of small world networks. © Springer-Verlag Berlin Heidelberg 2006.
Cite
CITATION STYLE
Li, J., Lv, R., Yang, Z., Yang, S., Mo, H., & Huang, X. (2006). Construction of small world networks based on K-Means clustering analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3991 LNCS-I, pp. 997–1000). Springer Verlag. https://doi.org/10.1007/11758501_157
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