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» A Genetic Algorithm for Clustering on Very Large Data Sets
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DEXAW
2010
IEEE
204views Database» more  DEXAW 2010»
13 years 9 months ago
Scalable Recursive Top-Down Hierarchical Clustering Approach with Implicit Model Selection for Textual Data Sets
Automatic generation of taxonomies can be useful for a wide area of applications. In our application scenario a topical hierarchy should be constructed reasonably fast from a large...
Markus Muhr, Vedran Sabol, Michael Granitzer
KDD
2002
ACM
1075views Data Mining» more  KDD 2002»
14 years 9 months ago
CLOPE: a fast and effective clustering algorithm for transactional data
This paper studies the problem of categorical data clustering, especially for transactional data characterized by high dimensionality and large volume. Starting from a heuristic m...
Yiling Yang, Xudong Guan, Jinyuan You
ESANN
2004
13 years 10 months ago
Fast semi-automatic segmentation algorithm for Self-Organizing Maps
Self-Organizing Maps (SOM) are very powerful tools for data mining, in particular for visualizing the distribution of the data in very highdimensional data sets. Moreover, the 2D m...
David Opolon, Fabien Moutarde
IJCAI
1997
13 years 10 months ago
Is Nonparametric Learning Practical in Very High Dimensional Spaces?
Many of the challenges faced by the £eld of Computational Intelligence in building intelligent agents, involve determining mappings between numerous and varied sensor inputs and ...
Gregory Z. Grudic, Peter D. Lawrence
TCAD
2002
110views more  TCAD 2002»
13 years 8 months ago
A constructive genetic algorithm for gate matrix layout problems
This paper describes an application of a Constructive Genetic Algorithm (CGA) to the Gate Matrix Layout Problem (GMLP). The GMLP happens in very large scale integration (VLSI) desi...
Alexandre César Muniz de Oliveira, Luiz Ant...