Role of Ranking Algorithms for Information Retrieval

TL;DR

This paper reviews various web page ranking algorithms, comparing their effectiveness in information retrieval, with a focus on PageRank and its variants, highlighting their roles in improving search engine relevance.

Contribution

It provides a comparative analysis of multiple page ranking algorithms, including PageRank, WPR, HITS, and others, emphasizing their differences and applications in web search.

Findings

PageRank is the core algorithm used by Google.

Weighted PageRank and other algorithms offer alternative ranking methods.

Simulation tools were developed for PageRank and Weighted PageRank.

Abstract

As the use of web is increasing more day by day, the web users get easily lost in the web's rich hyper structure. The main aim of the owner of the website is to give the relevant information according their needs to the users. We explained the Web mining is used to categorize users and pages by analyzing user's behavior, the content of pages and then describe Web Structure mining. This paper includes different Page Ranking algorithms and compares those algorithms used for Information Retrieval. Different Page Rank based algorithms like Page Rank (PR), WPR (Weighted Page Rank), HITS (Hyperlink Induced Topic Selection), Distance Rank and EigenRumor algorithms are discussed and compared. Simulation Interface has been designed for PageRank algorithm and Weighted PageRank algorithm but PageRank is the only ranking algorithm on which Google search engine works.