A Parallel Algorithm for Mining Non-Redundant Recurrent Rules from a Sequence Database

Abstract

We propose a parallel algorithm for mining non-redundant recurrent rules from a sequence database. Recurrent rules, proposed by Lo et al. [1], can express “Whenever a series of precedent events occurs, eventually a series of consequent events occurs,” and they have shown the usefulness of recurrent rules in various domains, including software specification and verification. Although some algorithms such as NR³ have been proposed, mining non-redundant recurrent rules still requires considerable processing time. To reduce the computation cost, we present a parallel approach to mining non-redundant recurrent rules, which fully utilizes the task-parallelism in NR³. We also give some experimental results, which show the effectiveness of our proposed method.