PPC: A novel approach of Chinese text mining based on Projection pursuit model

被引：0

作者：

Geng, Xinqing ^{[1
,2
]}

Ma, Zongmin ^{[2
]}

机构：

[1] Anshan Normal Univ, Coll Math & Informat Sci, Anshan, Peoples R China

[2] Northeastern Univ, Coll Informat Sci & Engn, Shenyang, Peoples R China

来源：

PROCEEDINGS OF 2014 IEEE WORKSHOP ON ADVANCED RESEARCH AND TECHNOLOGY IN INDUSTRY APPLICATIONS (WARTIA) | 2014年

关键词：

projection pursuit model; text clustering; data mining;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

A new fuzzy clustering algorithm (PPC) based on project pursuit model is presented in the paper. The main defect of the traditional clustering algorithm is to reduce dimension, while PPC don't need reduce dimension. Firstly, the text vector is normalized; Secondly, the project index function is constructed; Thirdly, the project function is optimized; Finally, the clustering result is acquired according to classification threshold. PPC algorithm improves the efficiency and precision of clustering.

引用

页码：950 / 952

页数：3