Application of Bayesian Model in Word Sense Disambiguation

Word Sense Disambiguation is developed to solve the problem of how to make the computer understand the meaning of some specific ambiguity in a specific context.Ambiguity is always frequently used.The most important task of word sense disambiguation is to establish an appropriate modeling method and select an effective way of machine learning.Bayesian model is relatively easy-to-use in the construction and realization,and the machine learning process is also simple and efficient.Especially Bayesian model,as a research tool for word sense disambiguation,is an ideal choice for its high efficiency and satisfying results.