Title :
Hyperlink Classification: A New Approach to Improve PageRank
Author :
Cun-He, Li ; Ke-Qiang, Lv
Author_Institution :
China Univ. of Pet., Dongying
Abstract :
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.
Keywords :
Internet; pattern classification; public domain software; search engines; Chinese Internet; NUTCH; PageRank; hyperlink classification; hypertext classification; link analysis; open source search engine; topic drift problem; Algorithm design and analysis; Application software; Cause effect analysis; Data engineering; Databases; Expert systems; Internet; Petroleum; Robustness; Search engines;
Conference_Titel :
Database and Expert Systems Applications, 2007. DEXA '07. 18th International Workshop on
Conference_Location :
Regensburg
Print_ISBN :
978-0-7695-2932-5
DOI :
10.1109/DEXA.2007.14