DMCA
Weighted Page-Rank algorithm (2004)
| Venue: | Communication Networks and Services Research, 2004. Proceedings. Second Annual Conference |
| Citations: | 77 - 0 self |
BibTeX
@INPROCEEDINGS{Xing04weightedpage-rank,
author = {Wenpu Xing and Ali Ghorbani},
title = {Weighted Page-Rank algorithm},
booktitle = {Communication Networks and Services Research, 2004. Proceedings. Second Annual Conference},
year = {2004}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
With the rapid growth of the Web, users get easily lost in the rich hyper structure. Providing relevant information to the users to cater to their needs is the primary goal of web-site owners. Therefore, finding the content of the Web and retrieving the users ’ interests and needs from their behav-ior have become increasingly important. Web mining is used to categorize users and pages by analyzing the users ’ be-havior, the content of the pages, and the order of the URLs that tend to be accessed in order. Web structure mining plays an important role in this approach. Two page rank-ing algorithms, HITS and PageRank, are commonly used in web structure mining. Both algorithms treat all links equally when distributing rank scores. Several algorithms have been developed to improve the performance of these methods. The Weighted PageRank algorithm (WPR), an ex-tension to the standard PageRank algorithm, is introduced in this paper. WPR takes into account the importance of both the inlinks and the outlinks of the pages and distributes rank scores based on the popularity of the pages. The results of our simulation studies show that WPR performs better than the conventional PageRank algorithm in terms of re-turning larger number of relevant pages to a given query.
Keyphrases
page-rank algorithm web structure mining rank score weighted pagerank algorithm web-site owner important role conventional pagerank algorithm several algorithm rapid growth relevant page user interest page rank-ing algorithm standard pagerank algorithm simulation study rich hyper structure web mining relevant information primary goal algorithm treat
