Title of article :
Inference with constrained hidden Markov models in PRISM
Author/Authors :
HENNING CHRISTIANSEN، نويسنده , , CHRISTIAN THEIL HAVE، نويسنده , , OLE TORP LASSEN and MATTHIEU PETIT، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2010
Abstract :
A Hidden Markov Model (HMM) is a common statistical model which is widely used for analysis of biological sequence data and other sequential phenomena. In the present paper we show how HMMs can be extended with side-constraints and present constraint solving techniques for efficient inference. Defining HMMs with side-constraints in Constraint Logic Programming has advantages in terms of more compact expression and pruning opportunities during inference. We present a PRISM-based framework for extending HMMs with side-constraints and show how well-known constraints such as cardinality and all.different are integrated. We experimentally validate our approach on the biologically motivated problem of global pairwise alignment.
Keywords :
programming in statistical modeling , inference , hidden Markov model with side-constraints
Journal title :
theory and practice of logic programming
Journal title :
theory and practice of logic programming