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

作者：Shiga Motoki^*; Takigawa Ichigaku; Mamitsuka Hiroshi

来源：Pattern Recognition, 2011, 44(2): 236-251.

DOI：10.1016/j.patcog.2010.08.010

• Semi-supervised clustering
• Heterogeneous data
• Data integration
• Spectral clustering

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.

• 出版日期2011-2