An Improved Association Rules Algorithm Based on Frequent Item Sets
نویسندگان
چکیده
منابع مشابه
Introduction to arules – Mining Association Rules and Frequent Item Sets
Mining frequent itemsets and association rules is a popular and well researched approach for discovering interesting relationships between variables in large databases. The R package arules presented in this paper provides a basic infrastructure for creating and manipulating input data sets and for analyzing the resulting itemsets and rules. The package also includes interfaces to two fast mini...
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Data mining, also known as Knowledge Discovery in Databases (KDD) is one of the most important and interesting research areas in 21 century. Frequent pattern discovery is one of the important techniques in data mining. The application includes Medicine, Telecommunications and World Wide Web. Nowadays frequent pattern discovery research focuses on finding co-occurrence relationships between item...
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Problem Statement: In today’s life, the mining of frequent patterns is a basic problem in data mining applications. The algorithms which are used to generate these frequent patterns must perform efficiently. The objective was to propose an effective algorithm which generates frequent patterns in less time. Approach: We proposed an algorithm which was based on hashing technique and combines a ve...
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ژورنال
عنوان ژورنال: Procedia Engineering
سال: 2011
ISSN: 1877-7058
DOI: 10.1016/j.proeng.2011.08.625