Research on Improved Algorithm of PageRank Based on Vector Space

被引：0

作者：

Tan, Xiangwei ^{[1
]}

Huang, Gengsheng ^{[2
]}

Jiang, Huiyong ^{[1
]}

机构：

[1] GU, South China Inst Software Engn, Guangzhou, Guangdong, Peoples R China

[2] Guangdong Vocat Inst Publ Adm, Guangzhou, Guangdong, Peoples R China

来源：

2ND INTERNATIONAL CONFERENCE ON COMPUTER ENGINEERING, INFORMATION SCIENCE AND INTERNET TECHNOLOGY, CII 2017 | 2017年

关键词：

Improved Algorithm; PageRank; Vector Space;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The traditional PageRank algorithm, which is based on the link analysis algorithm, considers the randomness of user access behavior, but the relevance of the query topic is poor. In order to improve the relevance of the page data search and acquisition, this paper proposes a PageRank algorithm based on the lucent vector space scoring model. The algorithm builds a vector space model based on the web content characteristics, calculates the similarity of the subject content, and combines the original PageRank algorithm, the new PR value is obtained after weighted fusion. Experiments show that the improved algorithm reduces the number of irrelevant pages, and the PR value can better reflect the relevance of the topic.

引用

页码：446 / 451

页数：6