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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