重庆理工大学学报（自然科学版）2017，Vol.31Issue(10)：175-179,197,6.DOI:10.3969/j.issn.1674-8425(z).2017.10.028
基于公共词块及N-gram模型的问句相似度算法
Question Similarity Algorithm Based on Common Chunks and N-Gram Model
摘要
Abstract
Question similarity algorithm is the key problem of QA,which directly affects the accuracy of QA.Aiming at the non applicability of the common chunks similarity algorithm (CCS) to Chinese text,an improved question similarity algorithm (CNS) is proposed,which combines the N-gram model and the common chunks to compute the similarity of the question vectors.The main idea is to break the question into unigram model and bigram model,then to analyze the common chunks between the questions and consider their sequential structure.Experimental results show that the new algorithm is better than the commonly used question similarity algorithms in the average similarity of Top-N data sets and the accuracy of different similarity threshold.关键词
问句相似度/N-gram模型/一元模型/公共词块Key words
question similarity/N-gram model/unigram model/common chunks分类
信息技术与安全科学引用本文复制引用
黄贤英,谢晋,龙姝言..基于公共词块及N-gram模型的问句相似度算法[J].重庆理工大学学报（自然科学版）,2017,31(10):175-179,197,6.基金项目
教育部人文社科青年项目(16YJC860010),重庆市社会科学规划博士项目(2015BS059) （16YJC860010）
