文档介绍：6
Association Analysis:
Basic Concepts and
Algorithms
Many business enterprises accumulate large quantities of data from their day-
to-day operations. For example, huge amounts of customer purchase data are
collected daily at the checkout counters of grocery stores. Table illustrates
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. Retail-
ers are interested in analyzing the data to learn about the purchasing behavior
of their customers. Such valuable information can be used to support a vari-
ety 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 associa-
Table . An example of market basket transactions.
TID Items
1 {Bread, Milk}
2 {Bread, Diapers, Beer, Eggs}
3 {Milk, Diapers, Beer, Cola}
4 {Bread, Milk, Diapers, Beer}
5 {Bread, Milk, Diapers, Cola}
328 Chapter 6 Association Analysis
tion rules or sets of frequent items. For example, the following rule can be
extracted from the data set shown in Table :
{Diapers}−→{Beer}.
The rule suggests that a strong relationship exists between the sale of diapers
and beer because many customers who buy diapers also buy beer. Retailers
can use this type of rules to help them identify new opportunities for cross-
selling their products to the customers.
Besides market basket data, association analysis is also applicable to other
application domains such as bioinformatics, medical diagnosis, Web mining,
and scientific data analysis. In the analysis of Earth science data, for example,
the association patterns may reveal interesting