Efficient mining strategy for frequent serial episodes in temporal database

Kuo Yu Huang, Chia Hui Chang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationFrontiers of WWW Research and Development - APWeb 2006 - 8th Asia-Pacific Web Conference, Proceedings
Pages824-829
Number of pages6
DOIs
StatePublished - 2006
Event8th Asia-Pacific Web Conference, APWeb 2006: Frontiers of WWW Research and Development - Harbin, China
Duration: 16 Jan 200618 Jan 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3841 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th Asia-Pacific Web Conference, APWeb 2006: Frontiers of WWW Research and Development
Country/TerritoryChina
CityHarbin
Period16/01/0618/01/06

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