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Multivariate statistics / Linear algebra / Matrix theory / Cluster analysis / Data analysis / Spectral clustering / Information bottleneck method / Eigenvalues and eigenvectors / K-means clustering / Algebra / Statistics / Mathematics


A Very Fast Method for Clustering Big Text Datasets Frank Lin and William W. Cohen 1 Abstract. Large-scale text datasets have long eluded a family of particularly elegant and effective clustering methods that exploits th
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Document Date: 2010-05-21 12:59:27

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Company

SIAM Journal / Cambridge University Press / Google / /

Country

United States / /

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IndustryTerm

k-means algorithm / iterative algorithm / peta-scale graph mining system / large-scale distributed computing environment / bipartite network / /

OperatingSystem

Linux / /

Organization

Cambridge University / National Institute of Health / National Science Foundation / idf / Carnegie Mellon / /

Person

Hongjie Bai / Ulrike von Luxburg / Frank Lin / Zoubin Ghahramani / Xiaojin Zhu / Arunabha Sen / Christos Faloutsos / Ling Huang / Marina Meil / Donghui Yan / Andrew Y. Ng / John Lafferty / David Woodruff / Michael I. Jordan / Naftali Tishby / Brian Kulis / Serge Belongie / Wen-Yen Chen / Yuqiang Guan / Chih-Jen Lin / Kang / Martin Szummer / Chung / Jianbo Shi / Edith Cohen / Miroslav Fiedler / Tom Roxborough / Inderjit S. Dhillon / Datasets Frank Lin / David D. Lewis / Michael Jordan / Yangqiu Song / William W. Cohen / Edward Y. Chang / Tony G. Rose / Yair Weiss / Christopher D. Manning / Hanson Zhou / Nick Crawell / Jitendra Malik / Noam Slonim / /

Technology

Lanczos algorithm / RAM / k-means algorithm / prior PIC algorithm / Linux / basic PIC algorithm / PIC algorithm / iterative algorithm / /

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