计算机工程2017，Vol.43Issue(9)：210-213,4.DOI:10.3969/j.issn.1000-3428.2017.09.037
基于依存句法分析的多特征词义消歧
Multi-feature Word Sense Disambiguation Based on Dependency Parsing Analysis
摘要
Abstract
Word Sense Disambiguation(WSD) plays an important role in machine translation,information retrieval and speech semantic recognition.In order to improve the quality of disambiguation and refine the feature,a multi-feature granularity WSD scheme is proposed.The extraction of parts of speech,dependency structure and dependent words is used to detail feature grain by dependency parsing.The weight function is constructed according to the multiple features as the classifier,and the meaning with the largest weight is chosen as the sense of the polysemous word.Experimental results show that compared with single feature WSD,the multi-feature WSD scheme based on dependency parsing refines the feature and improves the accuracy of disambiguation.关键词
词义消歧/依存句法/细化特征/多特征/权值Key words
Word Sense Disambiguation (WSD)/dependency parsing/detailed feature/mulit-feature/weight分类
信息技术与安全科学引用本文复制引用
史兆鹏,邹徐熹,向润昭..基于依存句法分析的多特征词义消歧[J].计算机工程,2017,43(9):210-213,4.基金项目
国家自然科学基金(61272540). （61272540）
