基于微博的用户相似度计算研究  

Computing Research of User Similarity Based on Micro-blog

作　　者：郑志蕴[1] 贾春园[1] 王振飞[1] 李钝[1] ZHENG Zhi-yun JIA Chun-yuan WANG Zhen-fei LI Dun(School of Information Engineering, Zhengzhou University, Zhengzhou 450001, China)

机构地区：[1]郑州大学信息工程学院,郑州450001

出　　处：《计算机科学》2017年第2期262-266,共5页Computer Science

基　　金：郑州大学新媒体公共传播学科招标课题(XMTGGCBJSZ05);河南省科技攻关项目(144300510007);郑州市科技攻关计划项目(141PPTGG368)资助

摘　　要：针对传统的相似度计算方法和评价标准在准确、高效地度量微博用户相似关系时不理想的缺陷,提出一种新的微博用户相似度的计算方法。该方法针对不同的属性数据结构采用不同的计算方式,并根据属性统计信息对各个属性赋值,利用层次分析法确定各属性权值,最后构建综合相似度计算模型。实验结果表明,相对于传统的相似度计算方法,所提计算方法衡量用户相似的准确度提高了22.6%,召回率提高了12.7%,F1度量值提高了29.5%。For traditional similarity calculation methods and evaluation criteria have defects that accurately and efficiently measuring micro-blog users similar relationship is undesirable,a new method to calculate micro-blog user similarity was proposed.For different attribute data structure,different calculation methods are used,and based on the assignment of property statistics for each property,the method uses AHP to determine the weight of each attribute,finally building an integrated similarity calculation model.Experimental results show that the improved method of calculation to measure user similarity precision increases by 22.6%,recall rate increases by 12.7%,and F1 metric improves 29.5%.

关 键 词：微博 用户相似度 属性权值 层次分析法 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]