Search Engine Optimization Algorithms for Page Ranking: Comparative Study

TLDR

The Web hosts over 11.3 billion pages and its rapid growth makes page ranking essential, yet search queries often return irrelevant results, creating overhead that degrades ranking quality. The study aims to develop a new optimization technique that reduces complexity and user overhead by presenting only relevant results to improve page ranking. To achieve this, the authors conduct a comparative analysis of existing page‑ranking algorithms and identify necessary improvements for search engine optimization. Simulation results demonstrate that current methods are insufficient, underscoring the need for a new optimization technique.

Abstract

Every second, the number of visitors increase day by day due to the fast growing of World Wide Web. Till this day there are more than 11.3 billion web pages in the World Wide Web. In the modern era of technology and advance computation, world page ranking become a common feature of modern retrieval system. However, any query in search engine will display both relevant and irrelevant data that can cause overhead to the search engine and will affect the page ranking process. A new optimization technique is needed to improve the existing search engine optimization in increasing the page ranking. This paper presents a comparative study of different page ranking algorithms for search engine optimization. Also it explores some improvements that are needed to overcome the current problem in this field. The simulation result’s analysis clearly shows that there is a need of new optimization technique. This new technique must reduce the complexity and user overhead by displaying only related data which will reduce overheading in search engine.