Hidden Markov models (HMMs) are powerful statistical models that have found successful applications in Information Extraction (IE). In current approaches to applying HMMs to IE, a...
Hidden Markov Models (HMMs) are one of the most fundamental and widely used statistical tools for modeling discrete time series. In general, learning HMMs from data is computation...
One important problem proposed recently in the field of web mining is website classification problem. The complexity together with the necessity to have accurate and fast algorit...
This paper presents a Hierarchical Context Hidden Markov Model (HC-HMM) for behavior understanding from video streams in a nursing center. The proposed HC-HMM infers elderly behav...
Background: The Generalized Hidden Markov Model (GHMM) has proven a useful framework for the task of computational gene prediction in eukaryotic genomes, due to its flexibility an...
William H. Majoros, Mihaela Pertea, Arthur L. Delc...