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» Algorithms for Clustering Data
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SDM
2004
SIAM
189views Data Mining» more  SDM 2004»
13 years 9 months ago
An Abstract Weighting Framework for Clustering Algorithms
act Weighting Framework for Clustering Algorithms Richard Nock Frank Nielsen Recent works in unsupervised learning have emphasized the need to understand a new trend in algorithmi...
Richard Nock, Frank Nielsen
SIGMOD
2001
ACM
200views Database» more  SIGMOD 2001»
14 years 8 months ago
Data Bubbles: Quality Preserving Performance Boosting for Hierarchical Clustering
In this paper, we investigate how to scale hierarchical clustering methods (such as OPTICS) to extremely large databases by utilizing data compression methods (such as BIRCH or ra...
Markus M. Breunig, Hans-Peter Kriegel, Peer Kr&oum...
ICDM
2002
IEEE
106views Data Mining» more  ICDM 2002»
14 years 28 days ago
Neighborgram Clustering Interactive Exploration of Cluster Neighborhoods
Proceedings of IEEE Data Mining, IEEE Press, pp. 581-584, 2002. We describe an interactive way to generate a set of clusters for a given data set. The clustering is done by constr...
Michael R. Berthold, Bernd Wiswedel, David E. Patt...
KDD
2005
ACM
135views Data Mining» more  KDD 2005»
14 years 8 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
ICDM
2005
IEEE
150views Data Mining» more  ICDM 2005»
14 years 1 months ago
Combining Multiple Clusterings by Soft Correspondence
Combining multiple clusterings arises in various important data mining scenarios. However, finding a consensus clustering from multiple clusterings is a challenging task because ...
Bo Long, Zhongfei (Mark) Zhang, Philip S. Yu