An Improved PageRank Algorithm Based on HowNet

摘要：

The traditional PageRank algorithm evaluates the importance of web pages through link relations between web pages and then ranks web pages. Because it only considers link relations between web pages, and ignores the relevance of the subject between web pages, web pages ranking quality is not high. In this paper, by full playing the HowNet characteristics of detailed describing semantic knowledge and revealing the relationship between concepts, I improved PageRank algorithm. The improved algorithm allocates PageRank value according to the semantic similarity of web page keywords in HowNet taxonomy tree. Through simulation experiments, the conclusion can be drawn that the new algorithm ranks more accurately than the traditional PageRank algorithm.

关键词： PageRank Semantic similarity HowNet Taxonomy

作者: Wenchao Li

作者单位: Liaoning Shihua University, School of Computer and Communication Engineering Fushun 113001 P.R China

会议类型: 国际会议

会议名称: 2010 International Conference on Information Technology and Industrial Engineering(2010年信息技术与工业工程国际学术会议 ITIE 2010)

会议地点: 武汉

会议语种:英文

页码: 721-724

在线出版日期: 2010-06-06（万方平台首次上网日期，不代表论文的发表时间）