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SDM
2009
SIAM
225views Data Mining» more  SDM 2009»
16 years 3 months ago
Integrated KL (K-means - Laplacian) Clustering: A New Clustering Approach by Combining Attribute Data and Pairwise Relations.
Most datasets in real applications come in from multiple sources. As a result, we often have attributes information about data objects and various pairwise relations (similarity) ...
Fei Wang, Chris H. Q. Ding, Tao Li
193
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DATAMINE
2006
224views more  DATAMINE 2006»
15 years 6 months ago
Characteristic-Based Clustering for Time Series Data
With the growing importance of time series clustering research, particularly for similarity searches amongst long time series such as those arising in medicine or finance, it is cr...
Xiaozhe Wang, Kate A. Smith, Rob J. Hyndman
SIGIR
2002
ACM
15 years 5 months ago
Document clustering with cluster refinement and model selection capabilities
In this paper, we propose a document clustering method that strives to achieve: (1) a high accuracy of document clustering, and (2) the capability of estimating the number of clus...
Xin Liu, Yihong Gong, Wei Xu, Shenghuo Zhu
ICWSM
2008
15 years 7 months ago
Clustering Tags in Enterprise and Web Folksonomies
Tags lack organizational structure limiting their utility for navigation. We present two clustering algorithms that improve this by organizing tags automatically. We apply the alg...
Edwin Simpson
CVPR
2004
IEEE
16 years 8 months ago
Spatially Coherent Clustering Using Graph Cuts
Feature space clustering is a popular approach to image segmentation, in which a feature vector of local properties (such as intensity, texture or motion) is computed at each pixe...
Ramin Zabih, Vladimir Kolmogorov