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In the past, the concept of performing the task of feature selection by attribute clustering was proposed. Hong et al. thus proposed several genetic algorithms for finding appropriate attribute clusters. In this paper, we attempt to improve the performance of the GA-based attribute-clustering process based on the grouping genetic algorithm (GGA). In our approach, the general GGA representation and...
Association rules are import basis of describing Web users' behavior characteristic. Traditional algorithms of Web association rules mining, based on statistics, usually pays attention to the analysis on existing data,they can't offer effective predictive means and optimizing measure and can not find out the latent and possible rules. This paper presents a kind of system of the Web association rules...
The high-order coclustering problem, i.e., the problem of simultaneously clustering heterogeneous types of domain, has become an active research area in the last few years, due to the notable impact it has on several application scenarios. This problem is generally faced by optimizing a weighted combination of functions measuring the quality of coclustering over each pair of domains, where weights...
This paper proposes a novel algorithm for signal classification problems. We consider a non-stationary random signal, where samples can be classified into several different classes, and samples in each class are identically independently distributed with an unknown probability distribution. The problem to be solved is to estimate the probability distributions of the classes and the correct membership...
This paper presents algorithm SCCMETreeMiner which can find all closed and maximal frequent embedded subtrees using length-decreasing support constraint. SCCMETreeMiner combines the rightmost path expansion scheme and projection technique to construct pattern growth space, and uses several techniques proposed in the paper to prune the branches of the enumeration trees that do not correspond to closed...
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