Research on parallelization of Apriori algorithm in association rule mining
نویسندگان
چکیده
منابع مشابه
Frequent Patterns for Mining Association Rule in Improved Apriori Algorithm
An important aspect of data mining is to discover association rules among large number of item sets. Association rules are if/then statements that help uncover relationships between seemingly unrelated data in a relational database or other information repository. The main problem is the generation of candidate set. In this thesis we have presented a different algorithm for mining frequent patt...
متن کاملAnalysis on Parallelization of Apriori Algorithm in Data Mining
Many algorithms are designed to analyse volumes of data automatically in an efficient way so that the users don’t have to look through that massive amount of data manually for generating various association rules among them. Apriori algorithm, which is the most famous and frequently used data mining algorithm. Our main focus is to parallelize the Apriori algorithm in such a new way that when we...
متن کاملEfficient Association Rule Mining Using Improved Apriori Algorithm
Association rule mining is a data mining technique to extract interesting relationships from large datasets [1, 2]. The efficiency of association rule mining algorithms has been a challenging research area in the domain of data mining [3]. Frequent pattern discovery, the task of finding sets of items that frequently occur together in a dataset is the most resource consuming phase of the rule mi...
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Association Rule Mining is an area of data mining that focuses on pruning candidate keys. An Apriori algorithm is the most commonly used Association Rule Mining. This algorithm somehow has limitation and thus, giving the opportunity to do this research. This paper introduces a new way in which the Apriori algorithm can be improved. The modified algorithm introduces factors such as set size and ...
متن کاملApriori Multiple Algorithm for Mining Association Rules
One of the most important data mining problems is mining association rules. In this paper we consider discovering association rules from large transaction databases. The problem of discovering association rules can be decomposed into two sub-problems: find large itemsets and generate association rules from large itemsets. The second sub-problem is easier one and the complexity of discovering as...
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ژورنال
عنوان ژورنال: Procedia Computer Science
سال: 2021
ISSN: 1877-0509
DOI: 10.1016/j.procs.2021.02.109