基于粗糙集特征加权的文本分类-浙江理工大学学报

文章信息/Info

Title:: Text Categorization by Feature Weighting Scheme Based on Rough Set

文章编号:: 16733851 (2011) 04054405

作者:: 徐欣; 黄理灿; 赵玉虹; 浙江理工大学信息电子学院，杭州 310018

Author(s):: XU Xin; HUANG Lican; ZHAO Yuhong; School of Informatics and Electronics, Zhejiang SciTech University, Hangzhou 310018, China

关键词:: ; 粗糙集理论; 特征加权; 文本分类; 近似分类精度; 近似分类质量

分类号:: TP301

文献标志码:: A

摘要:: 文本分类是当今信息检索和数据挖掘等领域的研究热点，而特征加权是文本分类过程中的重要步骤。为了提高分类质量，文章通过深入分析粗糙集理论和逆文本频率加权的思想，提出了一种基于粗糙集的特征加权方法，从近似分类精度和近似分类质量两个方面考虑特征词对分类的全局作用，将文本的类别属性信息引入到权重中。通过文本分类实验证明，该加权方法有助于提高分类系统的分类效果。

参考文献/References:

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［7］ Huang Lican, Xu Xin, Zhao Yuhong, et al. Feature weighting scheme for text categorization based on rough Set［C］//The First International Conference on Networking and Distributed Computing(ICNDC2010), 2010: 186188.
［8］ Yang Yiming, Liu Xin. A reexamination of text categorization methods

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浙江理工大学学报[ISSN:1673-3851/CN:33-1338/TS]

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