Clustering suggestion for Chinese news web pages from multi-media sources

被引：0
|
作者：
Chiu, Deng-Yiv [1 ]
Pan, Ya-Chen [1 ]
机构：
[1] Chung Hua Univ, Dept Informat Management, Hsinchu, Taiwan
来源：
PROCEEDINGS OF 2009 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND COMPUTING (IACSIT ICMLC 2009) | 2009年
关键词：
Chinese web pages clustering; multi-class SVM; fuzzy c-means algorithm; genetic algorithm;
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：
There exist some news obviously classified into incorrect categories on Chinese web pages portal. The main reasons could be that it is difficult to automatically classify Chinese news and the news appearing on web pages portal are retrieved from many media sources. In this study, we integrate genetic algorithm and multi-class support vector machine (SVM) classifier to construct a Chinese news classification method. In addition, we find that some similar documents are scattered in different categories. The main reason could be that the categories of original media sources are different from those of news web pages portal. Those similar news should be collected to form a new category. We try to combine genetic algorithm and fuzzy c-means algorithm to propose a new approach to offer clustering suggestion for news web pages that are scattered in different categories and are from multi-media sources.
引用
收藏
页码：183 / 187
页数：5
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