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» Categorizing Vulnerabilities Using Data Clustering Technique...
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PARA
2004
Springer
15 years 2 months ago
HPC-ICTM: The Interval Categorizer Tessellation-Based Model for High Performance Computing
Abstract. This paper presents the Interval Categorizer Tessellationbased Model (ICTM) for the simultaneous categorization of geographic regions considering several characteristics ...
Marilton S. de Aguiar, Graçaliz Pereira Dim...
KDD
1999
ACM
166views Data Mining» more  KDD 1999»
15 years 1 months ago
CACTUS - Clustering Categorical Data Using Summaries
Clustering is an important data mining problem. Most of the earlier work on clustering focussed on numeric attributes which have a natural ordering on their attribute values. Rece...
Venkatesh Ganti, Johannes Gehrke, Raghu Ramakrishn...
IADIS
2009
14 years 7 months ago
Trash article detection using categorization techniques
We explore techniques for detecting news articles containing invalid information, using the help of text categorization technology. The information that exists on the World Wide W...
Christos Bouras, Vassilis Tsogkas, Vassilis Poulop...
100
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ICDM
2008
IEEE
118views Data Mining» more  ICDM 2008»
15 years 3 months ago
Extension of Partitional Clustering Methods for Handling Mixed Data
Clustering is an active research topic in data mining and different methods have been proposed in the literature. Most of these methods are based on the use of a distance measure ...
Yosr Naïja, Salem Chakhar, Kaouthar Blibech, ...
ICDM
2005
IEEE
138views Data Mining» more  ICDM 2005»
15 years 3 months ago
Labeling Unclustered Categorical Data into Clusters Based on the Important Attribute Values
Sampling has been recognized as an important technique to improve the efficiency of clustering. However, with sampling applied, those points which are not sampled will not have t...
Hung-Leng Chen, Kun-Ta Chuang, Ming-Syan Chen