Predicting the Semantic Related words based on Hidden Markov Model
Fuping Yang, Huafeng Gu · 2016
This paper presents a method of predicting the words with semantic relation based on Hidden Markov Model (HMM).Two words are set as an observation sequence, combined with HMM and the corpus, which has taken some works in Natural Language Processing, to calculate the most probable sequence with semantic relation by the given observation sequence.By Reducing the impact of high frequency words on the traditional method of semantic prediction based on the Text-window Co-occurrence.The experiment results show that this method is effective.