Approximate N-Gram Markov Model for Natural Language Generation
Hsin-Hsi Chen and Yue-Shi Lee
Department of Computer Science and Information Engineering
National Taiwan University
Taipei, Taiwan, R.O.C.
Abstract
This paper proposes an Approximate n-gram Markov Model for bag generation.
Directed word association pairs with distances are used to approximate
(n-1)-gram and n-gram training tables. This model has parameters of word
association model, and merits of both word association model and Markov Model.
The training knowledge for bag generation can be also applied to lexical
selection in machine translation design.