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The association rule mining algorithm Apriori need to repeatedly scan the transaction database and a lot of I/O loads, moreover it may generate huge candidate sets, the complexity of time and space is relatively high. Aiming at the limitation of the algorithm, an algorithm is proposed for association rule mining based on matching array. The algorithm only needs to scan the database once, screens out...
Genetic Algorithm and Association Rules both are commonly used methods in data mining. In this paper, a brief overview of Genetic Algorithm and Association Rules has been given, and this paper has presented an improved extract method of association rules of genetic algorithm based on their respective advantages and disadvantages. It also did some research on designing encoding methods, structuring...
To mine popular accessed Web pages items and find out their association rule from the Web server Log database for junior users providing recommendation service. A novel GEP-based algorithm for mining multiple-layers association rules was presented. Firstly, takes generalizing technology as a way to value fitness function in GEP (Gene Expression Programming). Then, relying on the significant self-search...
This paper presents the G3PARM algorithm for mining representative association rules. G3PARM is an evolutionary algorithm that uses G3P (Grammar Guided Genetic Programming) and an auxiliary population made up of its best individuals who will then act as parents for the next generation. Due to the nature of G3P, the G3PARM algorithm allows us to obtain valid individuals by defining them through a context-free...
Genetic algorithm is an important algorithm of association rule mining. However, there is some issues that genetic algorithm easy to lead prematuring convergence and into the plight of local optimum, or convergence too much time and consume a large amount of time to search. For resolving this issues, the paper improves the algorithm through adopting an adaptive mutation rate and improving the methods...
Knowledge is a valuable asset to most organizations as a substantial source to support better decisions. Recently there has been an increasing interest in devising database and data mining technologies to automatically induce knowledge from biomedicine, clinical and health data. Most work had adopted a single technique in the knowledge induction process. We propose a knowledge mining system as an...
The vertical association rules mining algorithm is an effective mining method recently, which makes use of support sets of frequent itemsets to calculate the support of candidate itemsets. It overcomes the disadvantages that Apriori and its relative algorithms produce large amount of candidate itemsets and require scanning database many times. The vertical association rules mining algorithm needs...
An important task in data analysis is the understanding of unexpected or atypical behaviors in a group of individuals. Which categories of individuals earn the higher salaries or, on the contrary, which ones earn the lower salaries? We present the problem of how data concerning atypical groups can be mined compared with a target quantitative attribute, like for instance the attribute ldquosalaryrdquo,...
Association rule mining has attracted wide attention in both research and application areas recently. The mining of multilevel association rules is one of the important branches of it. In most of the studies, multilevel rules will be mined through repeated mining from databases or mining the rules at each individually levels, it affects the efficiency, integrality and accuracy. In this paper, a novel...
The problem of discovery association rules in large databases is considered. An encoding method for converting large databases to small one is proposed. Significant efficiency is obtained by applying some modified known algorithm on our proposed database layout. In addition, a new algorithm based on the proposed encoding method is introduced. Using some properties of numbers our database converts...
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