A spectral approach to clustering numerical vectors as nodes in a network

Authors:
Motoki Shiga;Ichigaku Takigawa;Hiroshi Mamitsuka
Affiliations:
Bioinformatics Center, Kyoto University, Gokasho, Uji 611-0011, Japan and Institute for Bioinformatics Research and Development (BIRD), Japan Science and Technology Agency (JST), Japan;Bioinformatics Center, Kyoto University, Gokasho, Uji 611-0011, Japan and Institute for Bioinformatics Research and Development (BIRD), Japan Science and Technology Agency (JST), Japan;Bioinformatics Center, Kyoto University, Gokasho, Uji 611-0011, Japan and Institute for Bioinformatics Research and Development (BIRD), Japan Science and Technology Agency (JST), Japan
Venue:
Pattern Recognition
Year:
2011

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Abstract

We address the issue of clustering examples by integrating multiple data sources, particularly numerical vectors and nodes in a network. We propose a new, efficient spectral approach, which integrates the two costs for clustering numerical vectors and clustering nodes in a network into a matrix trace, reducing the issue to a trace optimization problem which can be solved by an eigenvalue decomposition. We empirically demonstrate the performance of the proposed approach through a variety of experiments, including both synthetic and real biological datasets.