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ICML
2005
IEEE
16 years 7 months ago
Semi-supervised graph clustering: a kernel approach
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are...
Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Ray...
ICDM
2009
IEEE
133views Data Mining» more  ICDM 2009»
16 years 23 days ago
On K-Means Cluster Preservation Using Quantization Schemes
This work examines under what conditions compression methodologies can retain the outcome of clustering operations. We focus on the popular k-Means clustering algorithm and we dem...
Deepak S. Turaga, Michail Vlachos, Olivier Versche...
167
Voted
SDM
2007
SIAM
152views Data Mining» more  SDM 2007»
15 years 7 months ago
HP2PC: Scalable Hierarchically-Distributed Peer-to-Peer Clustering
In distributed data mining models, adopting a flat node distribution model can affect scalability. To address the problem of modularity, flexibility and scalability, we propose...
Khaled M. Hammouda, Mohamed S. Kamel
INTR
2010
157views more  INTR 2010»
15 years 4 months ago
Classifying the user intent of web queries using k-means clustering
Purpose – Web search engines are frequently used by people to locate information on the Internet. However, not all queries have an informational goal. Instead of information, so...
Ashish Kathuria, Bernard J. Jansen, Carolyn Hafern...
AUSAI
2009
Springer
16 years 21 days ago
A Graph Distance Based Structural Clustering Approach for Networks
In the era of information explosion, structured data emerge on a large scale. As a description of structured data, network has drawn attention of researchers in many subjects. Netw...
Xin Su, Chunping Li