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KDD
2005
ACM
135views Data Mining» more  KDD 2005»
16 years 3 months ago
A hybrid unsupervised approach for document clustering
We propose a hybrid, unsupervised document clustering approach that combines a hierarchical clustering algorithm with Expectation Maximization. We developed several heuristics to ...
Mihai Surdeanu, Jordi Turmo, Alicia Ageno
114
Voted
CIARP
2004
Springer
15 years 9 months ago
Parallel Algorithm for Extended Star Clustering
In this paper we present a new parallel clustering algorithm based on the extended star clustering method. This algorithm can be used for example to cluster massive data sets of do...
Reynaldo Gil-García, José Manuel Bad...
PAKDD
2009
ACM
123views Data Mining» more  PAKDD 2009»
15 years 8 months ago
Clustering with Lower Bound on Similarity
We propose a new method, called SimClus, for clustering with lower bound on similarity. Instead of accepting k the number of clusters to find, the alternative similarity-based app...
Mohammad Al Hasan, Saeed Salem, Benjarath Pupacdi,...
150
Voted
PAKDD
2000
ACM
124views Data Mining» more  PAKDD 2000»
15 years 7 months ago
Feature Selection for Clustering
In clustering, global feature selection algorithms attempt to select a common feature subset that is relevant to all clusters. Consequently, they are not able to identify individu...
Manoranjan Dash, Huan Liu
100
Voted
CSREASAM
2007
15 years 5 months ago
Survey of Supercomputer Cluster Security Issues
- The authors believe that providing security for supercomputer clusters is different from providing security for stand-alone PCs. The types of programs that supercomputer clusters...
George Markowsky, Linda Markowsky