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PAKDD
2007
ACM
158views Data Mining» more  PAKDD 2007»
14 years 1 months ago
Density-Sensitive Evolutionary Clustering
In this study, we propose a novel evolutionary algorithm-based clustering method, named density-sensitive evolutionary clustering (DSEC). In DSEC, each individual is a sequence of ...
Maoguo Gong, Licheng Jiao, Ling Wang, Liefeng Bo
EDM
2010
129views Data Mining» more  EDM 2010»
13 years 9 months ago
Skill Set Profile Clustering: The Empty K-Means Algorithm with Automatic Specification of Starting Cluster Centers
While students' skill set profiles can be estimated with formal cognitive diagnosis models [8], their computational complexity makes simpler proxy skill estimates attractive [...
Rebecca Nugent, Nema Dean, Elizabeth Ayers
DMKD
1997
ACM
308views Data Mining» more  DMKD 1997»
13 years 11 months ago
A Fast Clustering Algorithm to Cluster Very Large Categorical Data Sets in Data Mining
Partitioning a large set of objects into homogeneous clusters is a fundamental operation in data mining. The k-means algorithm is best suited for implementing this operation becau...
Zhexue Huang
SIGIR
2000
ACM
13 years 11 months ago
An investigation of linguistic features and clustering algorithms for topical document clustering
We investigate four hierarchical clustering methods (single-link, complete-link, groupwise-average, and single-pass) and two linguistically motivated text features (noun phrase he...
Vasileios Hatzivassiloglou, Luis Gravano, Ankineed...
ICDM
2009
IEEE
153views Data Mining» more  ICDM 2009»
13 years 5 months ago
A New Clustering Algorithm Based on Regions of Influence with Self-Detection of the Best Number of Clusters
Clustering methods usually require to know the best number of clusters, or another parameter, e.g. a threshold, which is not ever easy to provide. This paper proposes a new graph-b...
Fabrice Muhlenbach, Stéphane Lallich