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2008

Learning Process Behavior with EDY: an Experimental Analysis

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Learning Process Behavior with EDY: an Experimental Analysis
This paper presents an extensive evaluation, on artificial datasets, of EDY, an unsupervised algorithm for automatically synthesizing a Structured Hidden Markov Model (S-HMM) from a database of sequences. The goal of EDY is capturing the stochastic process by which the observed data was generated. The SHMM is a sub-class of Hidden Markov Model that exhibits a quasi-linear computational complexity and is well suited to real-time problems of process/user profiling.
Ugo Galassi
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2008
Where STAIRS
Authors Ugo Galassi
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