Hyperlink classification: A new approach to improve PageRank

被引：3

作者：

Cun-He, Li ^{[1
]}

Ke-qiang, Lv ^{[1
]}

机构：

[1] China Univ Petr, Sch Comp & Commun Engn, Donying 257061, Peoples R China

来源：

DEXA 2007: 18TH INTERNATIONAL CONFERENCE ON DATABASE AND EXPERT SYSTEMS APPLICATIONS, PROCEEDINGS | 2007年

关键词：

D O I：

10.1109/DEXA.2007.14

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Hyperlink Structure is widely used in the hypertext classification, but it has not been paid enough attention. We propose a hyperlink classification approach to improve PageRank algorithm which is widely used in the link analysis of search engine. The cause of the topic drift problem is analyzed and the hyperlinks are classified according to their creating motivations and effects. The improved PageRank algorithm is implemented on the open source search engine NUTCH in Chinese Internet. The experimental results show that the improved PageRank algorithm performs better than the standard PageRank.

引用

页码：274 / +

页数：2

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