A text mining agents based architecture for personal e-mail filtering and management - 文章详情页

作者：

Zhong, N. (Zhong, N..) | Matsunaga, T. (Matsunaga, T..) | Liu, C. (Liu, C..) (学者：刘超)

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Scopus

摘要：

E-mail　messages　can　be　modeled　as　semi-structured　documents　that　consist　of　a　set　of　classes　and　a　number　of　variable　length　free-text.　Thus,　many　text　mining　techniques　can　be　used　to　develop　a　personal　e-mail　filtering　and　management　system.　This　paper　addresses　a　text　mining　agents　based　architecture,　in　which　two　kinds　of　text　mining　agents:　USPC　(uncertainty　sampling　based　probabilistic　classifier)　and　R2L　(rough　relation　learning)　are　used　cooperatively,　for　personal　e-mail　filtering　and　management.　©　Springer-Verlag　Berlin　Heidelberg　2002.

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作者机构：

[ 1 ] [Zhong, N.]Dept. of Information Eng, Maebashi Institute of Technology, 460-1 Kamisadori-Cho, Maebashi-City, 371-0816, Japan
[ 2 ] [Matsunaga, T.]Dept. of Information Eng, Maebashi Institute of Technology, 460-1 Kamisadori-Cho, Maebashi-City, 371-0816, Japan
[ 3 ] [Liu, C.]School of Computer Science, Beijing Polytechnic University, Beijing, 100022, China

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