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What is Apriori Alorithm

Handbook of Research on Emerging Rule-Based Languages and Technologies: Open Solutions and Approaches
The seminal algorithm for mining frequent itemsets for Boolean association rules based on Apriori property
Published in Chapter:
Mining Association Rules
Mihai Gabroveanu (University of Craiova, Romania)
DOI: 10.4018/978-1-60566-402-6.ch027
Abstract
During the last years the amount of data stored in databases has grown very fast. Data mining, also known as knowledge discovery in databases, represents the discovery process of potentially useful hidden knowledge or relations among data from large databases. An important task in the data mining process is the discovery of the association rules. An association rule describes an interesting relationship between different attributes. There are different kinds of association rules: Boolean (crisp) association rules, quantitative association rules, fuzzy association rules, etc. In this chapter, we present the basic concepts of Boolean and the fuzzy association rules, and describe the methods used to discover the association rules by presenting the most important algorithms.
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