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Multiview Data Clustering by using Adaptive Spectral Co-clustering
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  • Journal title : Journal of KIISE
  • Volume 43, Issue 6,  2016, pp.686-691
  • Publisher : Korean Institute of Information Scientists and Engineers
  • DOI : 10.5626/JOK.2016.43.6.686
 Title & Authors
Multiview Data Clustering by using Adaptive Spectral Co-clustering
Son, Jeong-Woo; Jeon, Junekey; Lee, Sang-Yun; Kim, Sun-Joong;
In this paper, we introduced the adaptive spectral co-clustering, a spectral clustering for multiview data, especially data with more than three views. In the adaptive spectral co-clustering, the performance is improved by sharing information from diverse views. For the efficiency in information sharing, a co-training approach is adopted. In the co-training step, a set of parameters are estimated to make all views in data maximally independent, and then, information is shared with respect to estimated parameters. This co-training step increases the efficiency of information sharing comparing with ordinary feature concatenation and co-training methods that assume the independence among views. The adaptive spectral co-clustering was evaluated with synthetic dataset and multi lingual document dataset. The experimental results indicated the efficiency of the adaptive spectral co-clustering with the performances in every iterations and similarity matrix generated with information sharing.
clustering;spectral clustering;multiview data;co-relation coefficient;
 Cited by
J. Son, J. Jeon, S. Lee, and S. Kim, "Adaptive Spectral Co-clustering for Multiview Data," Proceedings of ICACT, pp. 447-450, 2016.

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