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PAKDD
2009
ACM
186views Data Mining» more  PAKDD 2009»
13 years 11 months ago
Pairwise Constrained Clustering for Sparse and High Dimensional Feature Spaces
Abstract. Clustering high dimensional data with sparse features is challenging because pairwise distances between data items are not informative in high dimensional space. To addre...
Su Yan, Hai Wang, Dongwon Lee, C. Lee Giles
SDM
2004
SIAM
253views Data Mining» more  SDM 2004»
13 years 6 months ago
Density-Connected Subspace Clustering for High-Dimensional Data
Several application domains such as molecular biology and geography produce a tremendous amount of data which can no longer be managed without the help of efficient and effective ...
Peer Kröger, Hans-Peter Kriegel, Karin Kailin...
TMM
2008
112views more  TMM 2008»
13 years 4 months ago
Multimodal News Story Clustering With Pairwise Visual Near-Duplicate Constraint
Story clustering is a critical step for news retrieval, topic mining, and summarization. Nonetheless, the task remains highly challenging owing to the fact that news topics exhibit...
Xiao Wu, Chong-Wah Ngo, Alexander G. Hauptmann
EMMCVPR
2001
Springer
13 years 9 months ago
Path Based Pairwise Data Clustering with Application to Texture Segmentation
Most cost function based clustering or partitioning methods measure the compactness of groups of data. In contrast to this picture of a point source in feature space, some data sou...
Bernd Fischer, Thomas Zöller, Joachim M. Buhm...
ICDM
2007
IEEE
137views Data Mining» more  ICDM 2007»
13 years 11 months ago
Locally Constrained Support Vector Clustering
Support vector clustering transforms the data into a high dimensional feature space, where a decision function is computed. In the original space, the function outlines the bounda...
Dragomir Yankov, Eamonn J. Keogh, Kin Fai Kan