哈尔滨工业大学学报（英文版）2005，Vol.12Issue(4)：408-414,7.
Chinese word sense disambiguation based on neural networks
Chinese word sense disambiguation based on neural networks
摘要
Abstract
The input of a network is the key problem for Chinese word sense disambiguation utilizing the neural network. This paper presents an input model of the neural network that calculates the mutual information between contextual words and the ambiguous word by using statistical methodology and taking the contextual words of a certain number beside the ambiguous word according to ( - M, + N). The experiment adopts triple-layer BP Neural Network model and proves how the size of a training set and the value of M and N affect the performance of the Neural Network Model. The experimental objects are six pseudowords owning three word-senses constructed according to certain principles. The tested accuracy of our approach on a closed-corpus reaches 90. 31% ,and 89. 62% on an open-corpus. The experiment proves that the Neural Network Model has a good performance on Word Sense Disambiguation.关键词
word sense disambiguation/artificial neural network/mutual information/pseudowordsKey words
word sense disambiguation/artificial neural network/mutual information/pseudowords分类
信息技术与安全科学引用本文复制引用
LIU Ting,LU Zhi-mao,LANG Jun,LI Sheng..Chinese word sense disambiguation based on neural networks[J].哈尔滨工业大学学报（英文版）,2005,12(4):408-414,7.基金项目
Sponsored by the National Natural Science Foundation of China( Grant No. 60435020). （ Grant No. 60435020）
