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» Categorization using semi-supervised clustering
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KDD
2005
ACM
124views Data Mining» more  KDD 2005»
14 years 8 months ago
CLICKS: an effective algorithm for mining subspace clusters in categorical datasets
We present a novel algorithm called Clicks, that finds clusters in categorical datasets based on a search for k-partite maximal cliques. Unlike previous methods, Clicks mines subs...
Mohammed Javeed Zaki, Markus Peters, Ira Assent, T...
KAIS
2006
164views more  KAIS 2006»
13 years 7 months ago
On efficiently summarizing categorical databases
Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its a...
Jianyong Wang, George Karypis
FSS
2008
130views more  FSS 2008»
13 years 7 months ago
A fuzzy k-partitions model for categorical data and its comparison to the GoM model
The grade of membership (GoM) model uses fuzzy sets as memberships of each individual to extreme profiles (or classes) on the likelihood function of multivariate multinomial distr...
Miin-Shen Yang, Yu-Hsuan Chiang, Chiu-Chi Chen, Ch...
MMM
2009
Springer
218views Multimedia» more  MMM 2009»
14 years 4 months ago
Sparse Multiscale Patches (SMP) for Image Categorization
Abstract. In this paper we address the task of image categorization using a new similarity measure on the space of Sparse Multiscale Patches (SMP). SMPs are based on a multiscale t...
Paolo Piro, Sandrine Anthoine, Eric Debreuve, Mich...
PARA
2004
Springer
14 years 29 days 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...