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» The Method of Quantum Clustering
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KDD
1998
ACM
80views Data Mining» more  KDD 1998»
15 years 10 months ago
Human Performance on Clustering Web Pages: A Preliminary Study
With the increase in information on the World Wide Web it has become difficult to quickly find desired information without using multiple queries or using a topic-specific search ...
Sofus A. Macskassy, Arunava Banerjee, Brian D. Dav...
SDM
2007
SIAM
122views Data Mining» more  SDM 2007»
15 years 8 months ago
Incremental Spectral Clustering With Application to Monitoring of Evolving Blog Communities
In recent years, spectral clustering method has gained attentions because of its superior performance compared to other traditional clustering algorithms such as K-means algorithm...
Huazhong Ning, Wei Xu, Yun Chi, Yihong Gong, Thoma...
SDM
2004
SIAM
212views Data Mining» more  SDM 2004»
15 years 8 months ago
Clustering with Bregman Divergences
A wide variety of distortion functions, such as squared Euclidean distance, Mahalanobis distance, Itakura-Saito distance and relative entropy, have been used for clustering. In th...
Arindam Banerjee, Srujana Merugu, Inderjit S. Dhil...
SDM
2003
SIAM
184views Data Mining» more  SDM 2003»
15 years 8 months ago
Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
Levent Ertöz, Michael Steinbach, Vipin Kumar
ICDM
2010
IEEE
230views Data Mining» more  ICDM 2010»
15 years 4 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