Date Added: Jan 2010
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.