Discovering Networks for Global Propagation of Influenza A (H3N2) Viruses by Clustering

Authors:
Kazuya Sata;Kouichi Hirata;Kimihito Ito;Tetsuji Kuboyama
Affiliations:
Department of Artificial Intelligence, Kyushu Institute of Technology, Iizuka, Japan 820-8502;Department of Artificial Intelligence, Kyushu Institute of Technology, Iizuka, Japan 820-8502;Research Center for Zoonosis Control, Hokkaido University, Sapporo, Japan 001-0020;Computer Center, Gakushuin University, Tokyo, Japan 171-8588
Venue:
KES '09 Proceedings of the 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems: Part II
Year:
2009

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Abstract

In this paper, we present a method of discovering networks for modeling global propagation of influenza A (H3N2) viruses using a clustering algorithm. First, we find the clusters for every region by using an agglomerative hierarchical clustering with complete linkage. Next, we collect similar virus clusters over all regions. Finally, by comparing the occurrence year of the similar clusters, we construct a directed graph as a propagation network among these virus clusters.