The feature extraction of text mining based on Web

被引：0
|
作者：
Liu, LZ [1 ]
Chen, JJ [1 ]
Song, HT [1 ]
机构：
[1] Beijing Inst Technol, Dept Comp, Beijing 100081, Peoples R China
来源：
ICEMI'2003: PROCEEDINGS OF THE SIXTH INTERNATIONAL CONFERENCE ON ELECTRONIC MEASUREMENT & INSTRUMENTS, VOLS 1-3 | 2003年
关键词：
Web; text mining; extract;
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：
A mass of information on WWW usually hides within Web electronic documents. So mining contents of Web pages is a kind of important application. Text mining depends on finding out feature set of documents. The text features are extracted by terms frequency based on Vector Space Model, and feature subset is selected according to evaluating function to reduce high vector dimensions. The selection of feature decides the efficiency of text mining.
引用
收藏
页码：547 / 550
页数：4
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