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.
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
Tel.: +1 703 830 6300
Fax: +1 703 830 2300 email@example.com
(Corporate matters and books only) IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042 firstname.lastname@example.org