计算机应用研究Issue(11)：3287-3290,4.DOI:10.3969/j.issn.1001-3695.2015.11.019
一种融合位置信息的字符串相似度度量方法
New method for calculating string similarity fusing location information
摘要
Abstract
Aimed at the limitation of traditional string similarity complex algorithm,this paper proposed an algorithm based on vector space model to calculate string similarity,which fused both character adjacent position relation and word order informa-tion.This method described adjacent degree through computing Hamming distance of vector in VSM.Then it figured out word order similarity based on vector Manhattan distance.Finally,the algorithm presented quantitative description to string similari-ty fusing the word order and character adjacent degree.Compared with the traditional method,the proposed algorithm decrea-ses the time complexity to O(n log(n)).Experimental results show that the method improves precision rate and gets more rea-sonable data result.关键词
字符串相似度/相邻字符/词序/汉明距离Key words
string similarity/adjacent character/word order/Hamming distance分类
信息技术与安全科学引用本文复制引用
肖雨,崔荣一,怀丽波..一种融合位置信息的字符串相似度度量方法[J].计算机应用研究,2015,(11):3287-3290,4.基金项目
延边大学延大科合字（2013）第12号项目 （）
