An Improved Centroid-based Approach for Multi-label Classification of Web Pages by Genre

被引:0
|
作者
Jebari, Chaker [1 ]
机构
[1] Coll Appl Sci, Ibri, Oman
来源
2011 23RD IEEE INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2011) | 2011年
关键词
multi-label classification; incremental classification; genre centroid; centroid adjustement; noise web page;
D O I
10.1109/ICTAI.2011.142
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we propose an improved multi-label approach to classify web pages by genre. Our approach provides a multi-label classification scheme in which a web page can be assigned to more than one genre. To deal with the rapid evolution of web genres, our approach implements an incremental centroid-based classification scheme. Conducted experiments on a multi-labeled corpus of web pages show that our approach provides good results.
引用
收藏
页码:889 / 890
页数:2
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