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» Mining Closed Episodes from Event Sequences Efficiently
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KDD
2007
ACM
182views Data Mining» more  KDD 2007»
14 years 6 months ago
A fast algorithm for finding frequent episodes in event streams
Frequent episode discovery is a popular framework for mining data available as a long sequence of events. An episode is essentially a short ordered sequence of event types and the...
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan
DIS
2009
Springer
14 years 10 days ago
Mining Frequent Bipartite Episode from Event Sequences
Takashi Katoh, Hiroki Arimura, Kouichi Hirata
ADBIS
2000
Springer
111views Database» more  ADBIS 2000»
13 years 10 months ago
Discovering Frequent Episodes in Sequences of Complex Events
Data collected in many applications have a form of sequences of events. One of the popular data mining problems is discovery of frequently occurring episodes in such sequences. Eff...
Marek Wojciechowski
KDD
2012
ACM
217views Data Mining» more  KDD 2012»
11 years 8 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
KDD
2008
ACM
217views Data Mining» more  KDD 2008»
14 years 6 months ago
Stream prediction using a generative model based on frequent episodes in event sequences
This paper presents a new algorithm for sequence prediction over long categorical event streams. The input to the algorithm is a set of target event types whose occurrences we wis...
Srivatsan Laxman, Vikram Tankasali, Ryen W. White