Data Management

VOGUE: A Variable Order Hidden Markov Model With Duration Based on Frequent Sequence Mining

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Executive Summary

The authors present VOGUE, a novel, variable order hidden Markov model with state durations, that combines two separate techniques for modeling complex patterns in sequential data: pattern mining and data modeling. VOGUE relies on a variable gap sequence mining method to extract frequent patterns with different lengths and gaps between elements. It then uses these mined sequences to build a variable order hidden Markov model, that explicitly models the gaps. The gaps implicitly model the order of the HMM, and they explicitly model the duration of each state.

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