In this paper, we describe our research into building an optimizer for association
rule queries. We present a framework of this query processor and report on the
progress of our research so far. An extended SQL syntax is used for expressing
association rule queries, and query trees of operators in an extended algebra
for their internal representation. The placement of constraints in the query
tree is discussed. We have developed an efficient algorithm called CT-ITL for
lower level implementation of frequent item set generation which is the most
critical step of association rule mining. The performance evaluations show that
our algorithm compares well with the most efficient algorithms available currently.
We also discuss further steps needed to reach our goal of integrating the optimizer
with database systems.