An Algorithm of Feature Selection and Feature Weighting Adjustment Based on Chinese Frame Net

被引：0

作者：

Zhao Xu ^{[1
]}

Liu Xi ^{[1
]}

Hao Xiaoyan ^{[1
]}

Liu Kaiying ^{[2
]}

机构：

[1] Taiyuan Univ Technol, Acad Comp & Software Engn, Taiyuan, Peoples R China

[2] Shanxi Univ, Sch Comp & Informat Technol, Taiyuan 030006, Peoples R China

来源：

PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOLS 1-9 | 2009年

关键词：

text categorization; feature selection; small training set; feature weighting adjustment; Chinese FrameNet;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The combination of TF and DF, which is used as the method of feature selection, and TF-IDF algorithm, which is used as feature weighting, are frequently used in the text categorization. But for a small training set, the combination of TF and DF will filter out many low-frequency words which have a strong capability of the feature discrimination. Hence the weight is directly influenced. In this paper, an algorithm of feature selection and feature weighting adjustment based on Chinese FrameNet (CFN) are presented which aims at solving the problem mentioned above. The experimental result indicates that the precision which is greater than the traditional algorithm can reach to 67.3% and can fits the small training set very well.

引用

页码：4300 / +

页数：3

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