Automatic Identification and Rule Mining for Relation Words of Chinese Compound Sentences Based on Bayesian Model
Yang Jin-ca · 2015
The compound sentence is an important unit of the Chinese sentence and its annotation is important to the research on comprehending Chinese texts.Identification of relation words is the basis of compound sentence annotation.Based on a comprehensive analysis of Chinese compounds corpus,this paper extracted features of relation words from their context and collocation.Those features are described in formulas.A combination of mutual information with information gains is used for selecting features and eliminating redundant features.The Bayesian model is used for training and testing feature sets.Rules are created from the statistics results,and rule base is configured with rules,which are used for automatic identification of relation words.The experimental results show that our method obtains a high accuracy in identification,which proves the feasibility and effectiveness of the method.