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» Dominant Sets and Pairwise Clustering
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ICPR
2008
IEEE
14 years 1 months ago
Unsupervised clustering using hyperclique pattern constraints
A novel unsupervised clustering algorithm called Hyperclique Pattern-KMEANS (HP-KMEANS) is presented. Considering recent success in semisupervised clustering using pair-wise const...
Yuchou Chang, Dah-Jye Lee, James K. Archibald, Yi ...
CVPR
2009
IEEE
15 years 2 months ago
Constrained Clustering via Spectral Regularization
We propose a novel framework for constrained spectral clustering with pairwise constraints which specify whether two objects belong to the same cluster or not. Unlike previous m...
Zhenguo Li (The Chinese University of Hong Kong), ...
CIKM
1999
Springer
13 years 11 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
2008
152views Data Mining» more  DMIN 2008»
13 years 8 months ago
PCS: An Efficient Clustering Method for High-Dimensional Data
Clustering algorithms play an important role in data analysis and information retrieval. How to obtain a clustering for a large set of highdimensional data suitable for database ap...
Wei Li 0011, Cindy Chen, Jie Wang
EOR
2008
99views more  EOR 2008»
13 years 7 months ago
Ordinal regression revisited: Multiple criteria ranking using a set of additive value functions
We present a new method, called UTAGMS , for multiple criteria ranking of alternatives from set A using a set of additive value functions which result from an ordinal regression. ...
Salvatore Greco, Vincent Mousseau, Roman Slowinski