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» Analyzing Harmonic Monitoring Data Using Data Mining
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SDM
2004
SIAM
212views Data Mining» more  SDM 2004»
14 years 11 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...
GD
2005
Springer
15 years 3 months ago
D-Dupe: An Interactive Tool for Entity Resolution in Social Networks
Visualizing and analyzing social networks is a challenging problem that has been receiving growing attention. An important first step, before analysis can begin, is ensuring that...
Mustafa Bilgic, Louis Licamele, Lise Getoor, Ben S...
KAIS
2006
126views more  KAIS 2006»
14 years 9 months ago
Fast and exact out-of-core and distributed k-means clustering
Clustering has been one of the most widely studied topics in data mining and k-means clustering has been one of the popular clustering algorithms. K-means requires several passes ...
Ruoming Jin, Anjan Goswami, Gagan Agrawal
ICPR
2006
IEEE
15 years 10 months ago
Finding Rule Groups to Classify High Dimensional Gene Expression Datasets
Microarray data provides quantitative information about the transcription profile of cells. To analyze microarray datasets, methodology of machine learning has increasingly attrac...
Jiyuan An, Yi-Ping Phoebe Chen
PKDD
2007
Springer
141views Data Mining» more  PKDD 2007»
15 years 3 months ago
Automatic Hidden Web Database Classification
In this paper, a method for automatic classification of Hidden-Web databases is addressed. In our approach, the classification tree for Hidden Web databases is constructed by tailo...
Zhiguo Gong, Jingbai Zhang, Qian Liu