TY  - CONF
ID  - kempe2008ipmu
T1  - Mining Temporal Patterns in an Automotive Environment
A1  - Kempe, Steffen
A1  - Kruse, Rudolf
ED  - Verdegay, José Luis
ED  - Ojeda-Aciego, Manuel
ED  - Magdalena, Luis
TI  - Proceedings of the International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU-08)
Y1  - 2008
SP  - 521
EP  - 528
T2  - University of Málaga
CY  - Málaga
KW  - frequent temporal patterns
KW  - industrial application
N2  - Mining frequent temporal patterns from interval-based data proved to be a valuable tool for generating knowledge in the automotive business. Many problems in our domain contain a temporal component and thus can be formulated by using interval sequences. In this paper we present three substantially different applications which can all be addressed by the same mining task: mining of frequent temporal patterns. We show that contemporary approaches for temporal pattern mining are not addressing this task sufficiently and present our algorithmic solution FSMTree. Further, we discuss the assessment of temporal rules which can be derived from the set of frequent patterns.
ER  -