计算机工程与应用2016，Vol.52Issue(3)：119-122,4.DOI:10.3778/j.issn.1002-8331.1402-0041
结合语义知识的汉语词义消歧
Chinese word sense disambiguation with semantic knowl-edge
摘要
Abstract
Word sense disambiguation is an important problem in natural language processing. In order to improve the precision of word sense disambiguation, semantic knowledge of left and right word units is mined starting from the target polysemous word. Based on the Bayesian model, a new method of word sense disambiguation is proposed with semantic information of left and right word units. SemEval-2007:Task#5 is used as training corpus and test corpus. The classifier of word sense disambiguation is optimized. Then the optimized classifier is tested. Experimental results show that the pre-cision of word sense disambiguation is improved.关键词
词义消歧/歧义词汇/贝叶斯模型/语义信息Key words
word sense disambiguation/polysemous word/Bayesian model/semantic information分类
信息技术与安全科学引用本文复制引用
张春祥,邓龙,高雪瑶,卢志茂..结合语义知识的汉语词义消歧[J].计算机工程与应用,2016,52(3):119-122,4.基金项目
国家自然科学基金(No.60903082) （No.60903082）
教育部春晖计划(No.S2009-1-15002) （No.S2009-1-15002）
中国博士后科学基金项目(No.2014M560249) （No.2014M560249）
黑龙江省自然科学基金(No.F2015041). （No.F2015041）
