Algorithms for computing association rules using a partial-support tree

This method uses a single pass of the database to perform a partial computation of support for all sets encountered in the database, storing this in the form of a set enumeration tree.

Abstract

This paper presents new algorithms for the extraction of association rules from binary databases. Most existing methods operate by generating “candidate” sets, representing combinations of attributes which may be associated, and then testing the database to establish the degree of association. This may involve multiple database passes, and is also likely to encounter problems when dealing with “dense” data due to the increase in the number of sets under consideration. Our method uses a single pass of the database to perform a partial computation of support for all sets encountered in the database, storing this in the form of a set enumeration tree. We describe algorithms for generating this tree and for using it to generate association rules.