Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. In data mining, association rule learning is a popular and well researched method for discovering interesting relations between variables in large databases. Piatetsky-Shapiro describes analyzing and presenting strong rules discovered in databases using different measures of interestingness. Based on the concept of strong rules, Agrawal et al. introduced association rules for discovering regularities between products in large scale transaction data recorded by point-of-sale (POS) systems in supermarkets. For example, the rule {onions, potatoes} Rightarrow {beef} found in the sales data of a supermarket would indicate that if a customer buys onions and potatoes together, he or she is likely to also buy beef.

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