Title
Mining Frequent Bipartite Episode from Event Sequences
Abstract
In this paper, first we introduce a bipartite episode of the form A ***B for two sets A and B of events, which means that every event of A is followed by every event of B . Then, we present an algorithm that finds all frequent bipartite episodes from an input sequence without duplication in O (|Σ| ·N ) time per an episode and in O (|Σ|2 n ) space, where Σ is an alphabet, N is total input size of $\mathcal S$, and n is the length of S . Finally, we give experimental results on artificial and real sequences to evaluate the efficiency of the algorithm.
Year
DOI
Venue
2009
10.1007/978-3-642-04747-3_13
Discovery Science
Keywords
DocType
Volume
event sequences,total input size,frequent bipartite episode,bipartite episode,input sequence,real sequence
Conference
5808
ISSN
Citations 
PageRank 
0302-9743
1
0.37
References 
Authors
14
3
Name
Order
Citations
PageRank
Takashi Katoh13911.29
Hiroki Arimura2113092.90
Kouichi Hirata313032.04