计算机应用研究2013，Vol.30Issue(9)：2672-2676,5.DOI:10.3969/j.issn.1001-3695.2013.09.028
基于图正则化MNMF的中文垃圾邮件过滤
Chinese spam filtering based on graph regularized MNMF algorithm
摘要
Abstract
Text e-mail data represented by vector space model (VSM) are high dimensionality.This situation is not conducive to construct e-mail filtering model.Therefore,dimensionality reduction need be performed.MNMF could simultaneously achieve dimensionality reduction and e-mail classification,and graph regularized NMF could keep the geometrical structure of the data space.Based on the above two improved NMF models,this paper put forward GMNMF algorithm,and designed an iterative solution algorithm.Using GMNMF algorithm and other related algorithm do Chinese spam filtering experiments.The experimental results show that the model of the proposed algorithm is superior to models of other good algorithms.关键词
向量空间模型/维数约减/最大间隔Semi-NMF/图正则化MNMF/中文垃圾邮件过滤Key words
vector space model (VSM) / dimensionality reduction/ MNMF/ GMNMF/ Chinese spam filtering分类
信息技术与安全科学引用本文复制引用
刘遵雄,黄志强,郑淑娟,石菲..基于图正则化MNMF的中文垃圾邮件过滤[J].计算机应用研究,2013,30(9):2672-2676,5.基金项目
国家自然科学基金资助项目(61065003) （61065003）
国家教育部人文社会科学研究规划基金资助项目(10YJC630379) （10YJC630379）
