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» Mining Sectorial Episodes from Event Sequences
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DIS
2006
Springer
13 years 9 months ago
Mining Sectorial Episodes from Event Sequences
In this paper, we introduce a sectorial episode of the form C r, where C is a set of events and r is an event. The sectorial episode C r means that every event of C is followed b...
Takashi Katoh, Kouichi Hirata, Masateru Harao
PAKDD
2010
ACM
215views Data Mining» more  PAKDD 2010»
13 years 7 months ago
Mining Closed Episodes from Event Sequences Efficiently
Recent studies have proposed different methods for mining frequent episodes. In this work, we study the problem of mining closed episodes based on minimal occurrences. We study the...
Wenzhi Zhou, Hongyan Liu, Hong Cheng
MDAI
2007
Springer
13 years 11 months ago
Mining Frequent Diamond Episodes from Event Sequences
In this paper, we introduce a diamond episode of the form s1 → E → s2, where s1 and s2 are events and E is a set of events. The diamond episode s1 → E → s2 means that every...
Takashi Katoh, Kouichi Hirata, Masateru Harao
KDD
2012
ACM
217views Data Mining» more  KDD 2012»
11 years 7 months ago
The long and the short of it: summarising event sequences with serial episodes
An ideal outcome of pattern mining is a small set of informative patterns, containing no redundancy or noise, that identifies the key structure of the data at hand. Standard freq...
Nikolaj Tatti, Jilles Vreeken