  In this paper, we propose an efficient algorithm for mining novel `Set of
Contrasting Rules'-pattern (SCR-pattern), which consists of several association
rules. This pattern is of high interest due to the guaranteed quality of the
rules forming it and its ability to discover useful knowledge. However,
SCR-pattern has no efficient mining algorithm. We propose SCR-Apriori
algorithm, which results in the same set of SCR-patterns as the
state-of-the-art approache, but is less computationally expensive. We also show
experimentally that by incorporating the knowledge about the pattern structure
into Apriori algorithm, SCR-Apriori can significantly prune the search space of
frequent itemsets to be analysed.
