Web page classification with an ant colony algorithm

被引：0
|
作者：
Holden, N [1 ]
Freitas, AA [1 ]
机构：
[1] Univ Kent, Comp Lab, Canterbury CT2 7NF, Kent, England
来源：
PARALLEL PROBLEM SOLVING FROM NATURE - PPSN VIII | 2004年 / 3242卷
关键词：
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
This paper utilizes Ant-Miner - the first Ant Colony algorithm for discovering classification rules - in the field of web content mining, and shows that it is more effective than C5.0 in two sets of BBC and Yahoo web pages used in our experiments. It also investigates the benefits and dangers of several linguistics-based text preprocessing techniques to reduce the large numbers of attributes associated with web content mining.
引用
收藏
页码：1092 / 1102
页数：11
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