Web Document Classification Using MFA and MPM

被引：0
作者：
Sun, Xia [1 ]
Wang, Ziqiang [1 ]
机构：
[1] Henan Univ Technol, Sch Informat Sci & Engn, Zhengzhou 450000, Peoples R China
来源：
2009 SECOND INTERNATIONAL CONFERENCE ON FUTURE INFORMATION TECHNOLOGY AND MANAGEMENT ENGINEERING, FITME 2009 | 2009年
关键词：
document classification; marginal fisher analysis(MFA); minimax probability machine(MPM); data mining;
D O I：
10.1109/FITME.2009.93
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Document classification has received extensive attention in the past decade due to its wide range applications. To efficiently deal with this problem, a novel document classification algorithm is proposed by using marginal fisher analysis(MFA) and minimax probability machine(MPM). Experimental results on the WebKB data set show that the proposed algorithm achieves much better performance than other related document classification algorithms.
引用
收藏
页码：349 / 352
页数：4
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