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GFKL
2007
Springer

FSMTree: An Efficient Algorithm for Mining Frequent Temporal Patterns

8 years 9 months ago
FSMTree: An Efficient Algorithm for Mining Frequent Temporal Patterns
Research in the field of knowledge discovery from temporal data recently focused on a new type of data: interval sequences. In contrast to event sequences interval sequences contain labeled events with a temporal extension. Mining frequent temporal patterns from interval sequences proved to be a valuable tool for generating knowledge in the automotive business. In this paper we propose a new algorithm for mining frequent temporal patterns from interval sequences: FSMTree. FSMTree uses a prefix tree data structure to efficiently organize all finite state machines and therefore dramatically reduces execution times. We demonstrate the algorithm's performance on field data from the automotive business.
Steffen Kempe, Jochen Hipp, Rudolf Kruse
Added 16 Aug 2010
Updated 16 Aug 2010
Type Conference
Year 2007
Where GFKL
Authors Steffen Kempe, Jochen Hipp, Rudolf Kruse
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