Implementation of a least fixpoint operator for fast mining of relational databases

Recent research has focused on computing large item sets for association rule mining using SQL3 least fixpoint computation, and by exploiting the monotonic nature of the SQL3 aggregate functions such as sum and create view recursive constructs. Such approaches allow us to view mining as an ad hoc querying exercise and treat the efficiency issue as an optimization problem. We present a recursive implementation of a recently proposed least fixpoint operator for computing large item sets from object-relational databases. We present experimental evidence to show that our implementation compares well with several well-regarded and contemporary algorithms for large item set generation.