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AAAI
2008
15 years 2 months ago
From Comparing Clusterings to Combining Clusterings
This paper presents a fast simulated annealing framework for combining multiple clusterings (i.e. clustering ensemble) based on some measures of agreement between partitions, whic...
Zhiwu Lu, Yuxin Peng, Jianguo Xiao
85
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SIGIR
2008
ACM
15 years 13 days ago
A comparative evaluation of different link types on enhancing document clustering
With a growing number of works utilizing link information in enhancing document clustering, it becomes necessary to make a comparative evaluation of the impacts of different link ...
Xiaodan Zhang, Xiaohua Hu, Xiaohua Zhou
PAMI
2008
197views more  PAMI 2008»
15 years 14 days ago
LEGClust - A Clustering Algorithm Based on Layered Entropic Subgraphs
Hierarchical clustering is a stepwise clustering method usually based on proximity measures between objects or sets of objects from a given data set. The most common proximity meas...
Jorge M. Santos, Joaquim Marques de Sá, Lu&...
CEC
2008
IEEE
15 years 7 months ago
A Quantum-inspired Genetic Algorithm for data clustering
—The conventional K-Means clustering algorithm must know the number of clusters in advance and the clustering result is sensitive to the selection of the initial cluster centroid...
Jing Xiao, YuPing Yan, Ying Lin, Ling Yuan, Jun Zh...
WWW
2008
ACM
15 years 12 days ago
A Novelty-based Clustering Method for On-line Documents
In this paper, we describe a document clustering method called noveltybased document clustering. This method clusters documents based on similarity and novelty. The method assigns...
Sophoin Khy, Yoshiharu Ishikawa, Hiroyuki Kitagawa