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Title:

Learning Probabilistc Real Time Automata From Multi-Attribute Event Logs

Document type:
Technical Report
Author(s):
Jana Schmidt; Stefan Kramer
Abstract:
The growing number of time-labeled datasets in science and industry increases the need for algorithms that automatically induce process models. Existing methods are capable of identifying process models that typically only work on single attribute events. We propose a new model type and its corresponding algorithm to address the problem of mining multi-attribute events, meaning that each event is described by a vector of attributes. The model is based on timed automata, includes expressive descr...     »
Keywords:
Probabilistic automata; multi-variate time series
Year:
2011
Year / month:
2011-10-10 00:00:00
Pages:
17
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