A partition enhanced mining algorithm for distributed association rule mining systems
نویسندگان
چکیده
منابع مشابه
Privacy-Preserving Distributed Association-Rule-Mining Algorithm
Data mining is a process that analyzes voluminous digital data in order to discover hidden but useful patterns from digital data. However, the discovering of such hidden patterns has statistical meaning and may often disclose some sensitive information. As a result, privacy becomes one of the prime concerns in the datamining research community. Since distributed association mining discovers ass...
متن کاملDistributed Association Rule Mining
Data mining is an iterative and interactive process that explores and analyzes voluminous digital data to discover valid, novel, and meaningful patterns (Mohammed, 1999). Since digital data may have terabytes of records, data mining techniques aim to find patterns using computationally efficient techniques. It is related to a subarea of statistics called exploratory data analysis. During the pa...
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متن کاملPartitioning strategies for distributed association rule mining
In this paper a number of alternative strategies for distributed/parallel association rule mining are investigated. The methods examined make use of a data structure, the T-tree, introduced previously by the authors as a structure for organising sets of attributes for which support is being counted. We consider six different approaches, representing different ways of parallelising the basic Apr...
متن کاملE-fwarm: Enhanced Fuzzy-based Weighted Association Rule Mining Algorithm
In the Association Rule Mining (ARM) approach, equal weight is assigned to all itemsets in the dataset. Hence, it is not appropriate for all datasets. The weight should be assigned based on the significance of each itemset. The WARM reduces extra steps during the generation of rules. As, the Weighted ARM (WARM) uses the significance of each itemset, it is applied in the data mining. The Fuzzy-b...
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ژورنال
عنوان ژورنال: Egyptian Informatics Journal
سال: 2015
ISSN: 1110-8665
DOI: 10.1016/j.eij.2015.06.006