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» An objective approach to cluster validation
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ICML
2005
IEEE
15 years 10 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...
ICPR
2006
IEEE
15 years 11 months ago
Multiple Objects Tracking with Multiple Hypotheses Graph Representation
We present a novel multi-object tracking algorithm based on multiple hypotheses about the trajectories of the objects. Our work is inspired by Reid's multiple hypothesis trac...
Alex Yong Sang Chia, Liyuan Li, Weimin Huang
CIKM
1999
Springer
15 years 2 months ago
Clustering Transactions Using Large Items
In traditional data clustering, similarity of a cluster of objects is measured by pairwise similarity of objects in that cluster. We argue that such measures are not appropriate f...
Ke Wang, Chu Xu, Bing Liu
DMIN
2006
151views Data Mining» more  DMIN 2006»
14 years 11 months ago
Rough Set Theory: Approach for Similarity Measure in Cluster Analysis
- Clustering of data is an important data mining application. One of the problems with traditional partitioning clustering methods is that they partition the data into hard bound n...
Shuchita Upadhyaya, Alka Arora, Rajni Jain
SDM
2009
SIAM
225views Data Mining» more  SDM 2009»
15 years 7 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