An Efficient Depth-first Search Algorithm for Extracting Frequent Diamond Episodes from Event Sequences

Abstract

In this paper, we study the problem of mining frequent diamond episodes efficientlyfrom an input event sequence with sliding a window. Here, a diamond episode is of the form a → E → b, which means that every event of E follows an event a and is followed by an event b. Then, we design a polynomial-delay and polynomial-space algorithm PolyFreqDmd that finds all of the frequent diamond episodes without duplicates from an event sequence in O(|Σ|²l) time per an episode and in O(|Σ|+l) space, where Σ and l are an alphabet and the length of the event sequence, respectively. Finally, we give experimental results on artificial and real-world event sequences with varying several mining parameters to evaluate the efficiency of the algorithm.