A reestimation algorithm for Probabilistic Recursive Transition Network

Authors:
Young S. Han;Key-Sun Choi
Affiliations:
Korea Advanced Institute of Science and Technology, Taejon, Korea;Korea Advanced Institute of Science and Technology, Taejon, Korea
Venue:
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 2
Year:
1994

Citing 2
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Abstract

Probabilistic Recursive Transition Network (PRTN) is an elevated version of RTN to model and process languages in stochastic parameters. The representation is a direct derivation from the RTN and keeps much the spirit of Hidden Markov Model at the same time. We present a resetination algorithm for PRTN that is a variation of Inside-Outside algorithm that computes the values of the probabilistic parameters from sample sentences (parsed or unparsed).