Mining frequent episodes from event sequences is an important topic in data mining fields with wide applications. Most of the existing researches focused on mining frequent episodes from a single event sequence. However, sequences containing simultaneous events are frequently encountered and we refer to such sequences as complex event sequences. Moreover, for some practical applications, users are often interested in target episodes where the last event of an episode is the target event type. In this paper, we address the problem of mining frequent target episodes in complex event sequences. We first extend the state-of-the-art algorithm PPS to be PPS+, which serves as a basic method for mining episodes from complex event sequences. Then, we propose a novel algorithm named TEM-SES (Target Episode Mining using Simultaneous Events Set) to overcome the drawback of PPS+. Experimental evaluation demonstrates that the proposed TEM-SES algorithm outperforms PPS+ substantially in terms of execution time and memory consumption.
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