NDLI: Multi-view clustering ensembles

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Proceedings. International Conference on Machine Learning and Cybernetics

Multi-view clustering ensembles

Content Provider	IEEE Xplore Digital Library
Author	Xijiong Xie Shiliang Sun
Copyright Year	2013
Description	Author affiliation: Dept. of Comput. Sci. & Technol., East China Normal Univ., Shanghai, China (Xijiong Xie; Shiliang Sun)
Abstract	Multi-view clustering and clustering ensembles have become increasingly popular in recent years. Multi-view clustering employs the relationship between views to cluster data; clustering ensembles combine different component clusterings to a better final partition. In this paper, we proposed the multi-view clustering ensembles which extend clustering ensembles to multi-view clustering. Experimental results show good performances of multi-view spectral clustering ensembles and multi-view kernel k-means clustering ensembles on real datasets.
Starting Page	51
Ending Page	56
File Size	585356
Page Count	6
File Format	PDF
ISBN	9781479902606
DOI	10.1109/ICMLC.2013.6890443
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Abstracts Ionosphere kernel k-means clustering multi-view clustering clustering ensembles spectral clustering
Content Type	Text
Resource Type	Article

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