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» A Coherent and Heterogeneous Approach to Clustering
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ICML
2007
IEEE
14 years 8 months ago
Adaptive dimension reduction using discriminant analysis and K-means clustering
We combine linear discriminant analysis (LDA) and K-means clustering into a coherent framework to adaptively select the most discriminative subspace. We use K-means clustering to ...
Chris H. Q. Ding, Tao Li
EDBTW
2004
Springer
14 years 1 months ago
Clustering Structured Web Sources: A Schema-Based, Model-Differentiation Approach
Abstract. The Web has been rapidly “deepened” with the prevalence of databases online. On this “deep Web,” numerous sources are structured, providing schema-rich data– Th...
Bin He, Tao Tao, Kevin Chen-Chuan Chang
IPPS
2003
IEEE
14 years 28 days ago
A Message Passing Interface Library for Inhomogeneous Coupled Clusters
Clusters of PC containing mostly general purpose hardware have become more and more usable for high performance computing tasks in the past few years. Clustering existing systems ...
Martin Pöppe, Silke Schuch, Thomas Bemmerl
SIGIR
2011
ACM
12 years 10 months ago
Collective topic modeling for heterogeneous networks
In this paper, we propose a joint probabilistic topic model for simultaneously modeling the contents of multi-typed objects of a heterogeneous information network. The intuition b...
Hongbo Deng, Bo Zhao, Jiawei Han
ICDM
2010
IEEE
230views Data Mining» more  ICDM 2010»
13 years 5 months ago
Clustering Large Attributed Graphs: An Efficient Incremental Approach
In recent years, many networks have become available for analysis, including social networks, sensor networks, biological networks, etc. Graph clustering has shown its effectivenes...
Yang Zhou, Hong Cheng, Jeffrey Xu Yu