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CIKM
2006
Springer
13 years 9 months ago
Efficiently clustering transactional data with weighted coverage density
In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...
Hua Yan, Keke Chen, Ling Liu
ICDE
2005
IEEE
132views Database» more  ICDE 2005»
14 years 1 months ago
CLICKS: Mining Subspace Clusters in Categorical Data via K-partite Maximal Cliques
We present a novel algorithm called CLICKS, that finds clusters in categorical datasets based on a search for kpartite maximal cliques. Unlike previous methods, CLICKS mines subs...
Mohammed Javeed Zaki, Markus Peters
ICPR
2008
IEEE
14 years 1 months ago
Categorization using semi-supervised clustering
Many applications require matching objects to a predefined, yet highly dynamic set of categories accompanied by category descriptions. We present a novel approach to solving this...
Jianying Hu, Moninder Singh, Aleksandra Mojsilovic
ICDE
2007
IEEE
129views Database» more  ICDE 2007»
14 years 1 months ago
Ontology-driven Rule Generalization and Categorization for Market Data
—Radio Frequency Identification (RFID) is an emerging technique that can significantly enhance supply chain processes and deliver customer service improvements. RFID provides use...
Dongwoo Won, Dennis McLeod
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...