Application of statistical learning methods in the senmantic disambiguation
Wenrong Tan · jOURNAL OF southwest University for Nationalities · 2007
The senmantic ambiguity widly exists in natural language.The accuracy rate of sense ambiguation is the most important target of a software in the fields of machine translation,information search and text classification.In this paper we probe into the techniques of senmantic disambiguation,which is the most difficult problem in the natural language understanding field.We analyse the application of statistical learning methods in the senmantic disambigution and expatiate the correlative technologies.Finally we give an example of senamantic disambiguation based on the bayes and machine readable dictionary which have a high accuracy rate.