A Simulation Based Comparative Analysis for Web Pages and Link Queries Using Web Ranking Algorithms

Abstract

In the realm of web information retrieval, the effectiveness of ranking algorithms plays a pivotal role in providing accurate and relevant search results. This simulation-based comparative analysis aims to explore the performance of two prominent ranking algorithms, namely PageRank and Weighted Page Ranking, in the context of web pages and link queries. By leveraging a comprehensive dataset comprising web pages and links, we conduct a meticulous simulation study to evaluate the effectiveness of these algorithms. Through iterative calculations and convergence analysis, we determine the rankings assigned to web pages based on their importance and connectivity within the web graph. The comparison is carried out using multiple evaluation metrics, including precision, recall, and mean average precision, to assess the algorithm’s performance in retrieving relevant web pages and handling link queries. The simulations provide valuable results of both PageRank and Weighted Page Ranking algorithms, shedding light on their applicability in various information retrieval scenarios. The performance of PageRank and Weighted PageRank algorithms can vary depending on the specific dataset, weighting factors and evaluation metrics used. The better algorithm in terms of results may depend on the particular goals and requirements of applications.