Association Analysis: Basic Concepts and Algorithms

Many business enterprises accumulate large quantities of data from their dayto-day operations. For example, huge amounts of customer purchase data are collected daily at the checkout counters of grocery stores. Table 5.1 gives an example of such data, commonly known as market basket transactions. Each row in this table corresponds to a transaction, which contains a unique identifier labeled TID and a set of items bought by a given customer. Retailers are interested in analyzing the data to learn about the purchasing behavior of their customers. Such valuable information can be used to support a variety of business-related applications such as marketing promotions, inventory management, and customer relationship management. This chapter presents a methodology known as association analysis, which is useful for discovering interesting relationships hidden in large data sets. The uncovered relationships can be represented in the form of sets of items present in many transactions, which are known as frequent itemsets,