现代电子技术2018，Vol.41Issue(11)：157-161,5.DOI:10.16652/j.issn.1004-373x.2018.11.035
基于向量空间模型结合语义的文本相似度算法
Text similarity algorithm combining semantics based on vector space model
冯高磊 1高嵩峰1
作者信息
- 1. 北京建筑大学 机电与车辆工程学院,北京 100044
- 折叠
摘要
Abstract
The semantics and structural relation of words are ignored in the vector space model method,and the practical meaning of word expression isn′t considered. Therefore,a new test similarity calculation method is proposed,which can integrate the calculation of semantic similarity into the text similarity algorithm based on vector space model. The similarity of semantics and vector space model is weighted to obtain the result of text similarity. The experimental results show that,in comparison with the vector space model method and available semantic similarity algorithm,the recall rate obtained by the proposed similarity algorithm is improved to different extents,which can prove the effectiveness of the algorithm.关键词
文本相似度/向量空间模型/语义/词频/召回率/特征项Key words
text similarity/vector space model/semantics/word frequency/recall rate/characteristic item分类
信息技术与安全科学引用本文复制引用
冯高磊,高嵩峰..基于向量空间模型结合语义的文本相似度算法[J].现代电子技术,2018,41(11):157-161,5.
