DocumentCode
2325044
Title
Mining sequences for patterns with non-repeating symbols
Author
Walicki, Michal ; Ferreira, Diogo R.
Author_Institution
Inst. of Inf., Univ. of Bergen, Bergen, Norway
fYear
2010
fDate
18-23 July 2010
Firstpage
1
Lastpage
8
Abstract
Finding the case id in unlabeled event logs is arguably one of the hardest challenges in process mining research. While this problem can be addressed with greedy approaches, these usually converge to sub-optimal solutions. In this paper, we describe an approach to perform complete search over the search space. We formulate the problem as a matter of finding the minimal set of patterns contained in a sequence, where patterns can be interleaved but do not have repeating symbols. We show that for practical purposes it is possible to reduce the search space to maximal disjoint occurrences of these patterns. Experimental results suggest that, whenever this approach finds a solution, it usually finds a minimal one.
Keywords
data mining; pattern recognition; sequences; system monitoring; complete search; greedy approach; nonrepeating symbols; process mining; search space; sequence pattern mining; unlabeled event logs;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation (CEC), 2010 IEEE Congress on
Conference_Location
Barcelona
Print_ISBN
978-1-4244-6909-3
Type
conf
DOI
10.1109/CEC.2010.5585995
Filename
5585995
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