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111
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GECCO
2003
Springer
15 years 8 months ago
Mining Comprehensible Clustering Rules with an Evolutionary Algorithm
In this paper, we present a novel evolutionary algorithm, called NOCEA, which is suitable for Data Mining (DM) clustering applications. NOCEA evolves individuals that consist of a ...
Ioannis A. Sarafis, Philip W. Trinder, Ali M. S. Z...
KDD
2006
ACM
150views Data Mining» more  KDD 2006»
16 years 3 months ago
Maximally informative k-itemsets and their efficient discovery
In this paper we present a new approach to mining binary data. We treat each binary feature (item) as a means of distinguishing two sets of examples. Our interest is in selecting ...
Arno J. Knobbe, Eric K. Y. Ho
SDM
2007
SIAM
117views Data Mining» more  SDM 2007»
15 years 4 months ago
Discriminating Subsequence Discovery for Sequence Clustering
In this paper, we explore the discriminating subsequencebased clustering problem. First, several effective optimization techniques are proposed to accelerate the sequence mining p...
Jianyong Wang, Yuzhou Zhang, Lizhu Zhou, George Ka...
KDD
2005
ACM
92views Data Mining» more  KDD 2005»
16 years 3 months ago
Summarizing itemset patterns: a profile-based approach
Frequent-pattern mining has been studied extensively on scalable methods for mining various kinds of patterns including itemsets, sequences, and graphs. However, the bottleneck of...
Xifeng Yan, Hong Cheng, Jiawei Han, Dong Xin
130
Voted
SAC
2004
ACM
15 years 8 months ago
Statistical properties of transactional databases
Most of the complexity of common data mining tasks is due to the unknown amount of information contained in the data being mined. The more patterns and correlations are contained ...
Paolo Palmerini, Salvatore Orlando, Raffaele Pereg...