ABSTRACT
This chapter introduces the algorithm of mining association rules. A list of software packages that support association rules is provided. Some applications of association rules are given with references. Association rules uncover items that are frequently associated together. The algorithm of association rules was initially developed in the context of market basket analysis for studying customer purchasing behaviors that can be used for marketing. Association rules uncover what items customers often purchase together. There are many other applications of association rules, for example, text analysis for document classification and retrieval. An item set contains a set of items. For example, a customer’s purchase transaction at a grocery store is an item set or a set of grocery items such as eggs, tomatoes, and apples. Association rule discovery is used to find all association rules that exceed the minimum thresholds on certain measures of association, typically support and confidence.
