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Research on Ranking Algorithms in Web Structure Mining

International Journal of Knowledge Based Computer Systems

Volume 3 Issue 2

Published: 2015
Author(s) Name: Suvarna Sharma, Amit Bhagat | Author(s) Affiliation: Mathematics & Comp. App. Dept., Maulana Azad National Inst. of Tech., Bhopal, Madhya Pradesh, India
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Abstract

In the past few decades, the Web has emerged as a treasure of information and web mining is a technique to handle this treasure. During recent years web mining has been a well-researched area. Web mining is the application of the data mining which is useful to extract the knowledge from web. With the progress of web, more and more data are now available for users on web. Web structure mining deals with the contents and hyperlinks on web pages. In this review paper, we have focused on three basic algorithms for evaluating the importance of pages i.e. Page Rank, Weighted Page Rank, and Hyperlink-Induced Topic Search and comparison of those algorithms. Page Rank algorithm is based on back links of the page and it calculates the rank of web pages at indexing time. Weighted Page Rank algorithm scores pages according to their relevancies and rank of a page is calculated by its number of incoming and outgoing links. Hyperlink-induced topic search algorithm is an iterative algorithm developed to quantify each pages value as an authority and as a hub. This study was done basically to explore the link structure algorithms for ranking pages.

Keywords: Web Mining, Web Structure Mining, Page Rank, Weighted Page Rank, Hyperlink-Induced Topic Search

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