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PAKDD
2007
ACM
158views Data Mining» more  PAKDD 2007»
15 years 6 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»
15 years 1 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»
15 years 4 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
15 years 4 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»
14 years 9 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