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

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.