Structured Hidden Markov Model (S-HMM) is a variant of Hierarchical Hidden Markov Model that shows interesting capabilities of extracting knowledge from symbolic sequences. In fact...
Discriminative learning techniques for sequential data have proven to be more effective than generative models for named entity recognition, information extraction, and other task...
In this paper, we consider the relationship between risksensitivity and information. Product estimators are introduced as a generalization of Maximum A Posteriori Probability (MAP...
Vahid Reza Ramezani, Steven I. Marcus, Michael C. ...
We present a new method for information retrievalusing hidden Markov models (HMMs). We develop a general framework for incorporating multiple word generation mechanisms within the...
We present a new method for information retrieval using hidden Markov models HMMs and relate our experience with this system on the TREC-7 ad hoc task. We develop a general framew...