@inproceedings{1023926b0d3f4b1a8d56fee2b5d2d986,
title = "Efficient mining strategy for frequent serial episodes in temporal database",
abstract = "Discovering patterns with great significance is an important problem in data mining discipline. A serial episode is defined to be a partially ordered set of events for consecutive and fixed-time intervals in a sequence. Previous studies on serial episodes consider only frequent serial episodes in a sequence of events (called simple sequence). In real world, we may find a set of events at each time slot in terms of various intervals (called complex sequence). Mining frequent serial episodes in complex sequences has more extensive applications than that in simple sequences. In this paper, we discuss the problem on mining frequent serial episodes in a complex sequence. We extend previous algorithm MINEPI to MINEPI+ for serial episode mining from complex sequences. Furthermore, a memory-anchored algorithm called EMMA is introduced for the mining task.",
author = "Huang, {Kuo Yu} and Chang, {Chia Hui}",
year = "2006",
doi = "10.1007/11610113_80",
language = "???core.languages.en_GB???",
isbn = "3540311424",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "824--829",
booktitle = "Frontiers of WWW Research and Development - APWeb 2006 - 8th Asia-Pacific Web Conference, Proceedings",
note = "8th Asia-Pacific Web Conference, APWeb 2006: Frontiers of WWW Research and Development ; Conference date: 16-01-2006 Through 18-01-2006",
}