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ERCIMDL
2000
Springer
147views Education» more  ERCIMDL 2000»
13 years 11 months ago
Map Segmentation by Colour Cube Genetic K-Mean Clustering
Segmentation of a colour image composed of different kinds of texture regions can be a hard problem, namely to compute for an exact texture fields and a decision of the optimum num...
Vitorino Ramos, Fernando Muge
EDBT
2008
ACM
167views Database» more  EDBT 2008»
14 years 7 months ago
HISSCLU: a hierarchical density-based method for semi-supervised clustering
In situations where class labels are known for a part of the objects, a cluster analysis respecting this information, i.e. semi-supervised clustering, can give insight into the cl...
Christian Böhm, Claudia Plant
IJIS
2008
123views more  IJIS 2008»
13 years 7 months ago
Algorithms of nonlinear document clustering based on fuzzy multiset model
Abstract: Fuzzy multiset is applicable as a model of information retrieval because it has the mathematical structure which expresses the number and the degree of attribution of an ...
Kiyotaka Mizutani, Ryo Inokuchi, Sadaaki Miyamoto
DEXA
2007
Springer
140views Database» more  DEXA 2007»
14 years 1 months ago
Clustering-Based K-Anonymisation Algorithms
Abstract. K-anonymisation is an approach to protecting private information contained within a dataset. Many k-anonymisation methods have been proposed recently and one class of suc...
Grigorios Loukides, Jianhua Shao
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 ...