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

页码：889 / 890

页数：2

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