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Multiview Clustering of Multilingual Documents

Young-Min Kim
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Cyril Goutte
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We propose a new multi-view clustering method which uses clustering results obtained on each view as a voting pattern in order to construct a new set of multi-view clusters. Our experiments on a multilingual corpus of documents show that performance increases significantly over simple concatenation and another multi-view clustering technique.

Dates and versions

hal-01292100 , version 1 (22-03-2016)



Young-Min Kim, Massih-Reza Amini, Cyril Goutte, Patrick Gallinari. Multiview Clustering of Multilingual Documents. The 33rd Annual ACM SIGIR Conference (SIGIR 2010), Jul 2010, Geneva, Switzerland. pp.812-822, ⟨10.1145/1835449.1835633⟩. ⟨hal-01292100⟩
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