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» k-Means Projective Clustering
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KDD
2009
ACM
611views Data Mining» more  KDD 2009»
14 years 8 months ago
Fast approximate spectral clustering
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
Donghui Yan, Ling Huang, Michael I. Jordan
ICDM
2007
IEEE
149views Data Mining» more  ICDM 2007»
14 years 2 months ago
Non-redundant Multi-view Clustering via Orthogonalization
Typical clustering algorithms output a single clustering of the data. However, in real world applications, data can often be interpreted in many different ways; data can have diff...
Ying Cui, Xiaoli Z. Fern, Jennifer G. Dy
IM
2007
13 years 7 months ago
Cluster Generation and Labeling for Web Snippets: A Fast, Accurate Hierarchical Solution
This paper describes Armil, a meta-search engine that groups the web snippets returned by auxiliary search engines into disjoint labeled clusters. The cluster labels generated by A...
Filippo Geraci, Marco Pellegrini, Marco Maggini, F...
ICMCS
2000
IEEE
79views Multimedia» more  ICMCS 2000»
14 years 13 days ago
From Features to Semantics: Some Preliminary Results
In this paper, we present the results of a project that seeks to transform low-level features to a higher level of meaning. This project concerns a technique, latent semantic anal...
Rong Zhao, William I. Grosky
CIKM
2008
Springer
13 years 10 months ago
A consensus based approach to constrained clustering of software requirements
Managing large-scale software projects involves a number of activities such as viewpoint extraction, feature detection, and requirements management, all of which require a human a...
Chuan Duan, Jane Cleland-Huang, Bamshad Mobasher