Research Paper on Apriori Algorithm
Apriori
algorithm is an algorithm for mining association rules.
In the area of ??data mining, the research of Association Rules is a popular study in depth with the aim of discovering relationships of interest to the statistician between two or more variables stored in very large databases. Piatetsky-Shapiro method presents association rules extremely strong discovered in databases using different measures of interest. Based on the concept of strong relationships, Rakesh Agrawal and his team present association rules whose purpose is to discover similarities between items in the data entered on a large scale in computer systems of sales points belonging to the supermarkets channels. For example, a rule found in the sales data in a supermarket could indicate a customer, purchasing onions and potatoes together, would be likely buying a hamburger. Such information can be used as basis for making marketing decisions, such as, for example, for promotions or well chosen placement of related products.
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In addition to the above examples for the food basket, association rules are employed today in many areas, including that of searching the web, the Intrusion Detection and Bioinformatics
The concept of association rule was popularized in particular an article by Rakesh Agrawal 1993. But it is possible that this notion was discovered as the GUHA in 1966 by Petr Hájek and his colleagues.
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