An Innovative Approach for online Meta Search Engine Optimization

TL;DR

This paper introduces an intelligent meta search engine that aggregates results from multiple search engines and uses multiple SEO parameters to improve ranking accuracy and user satisfaction.

Contribution

It develops a novel meta search engine that incorporates multiple SEO factors into ranking, outperforming existing search engines in result quality.

Findings

Meta search engine achieved higher precision in search results.

Using multiple SEO parameters improves search result relevance.

Initial tests show better performance than existing search engines.

Abstract

This paper presents an approach to identify efficient techniques used in Web Search Engine Optimization (SEO). Understanding SEO factors which can influence page ranking in search engine is significant for webmasters who wish to attract large number of users to their website. Different from previous relevant research, in this study we developed an intelligent Meta search engine which aggregates results from various search engines and ranks them based on several important SEO parameters. The research tries to establish that using more SEO parameters in ranking algorithms helps in retrieving better search results thus increasing user satisfaction. Initial results generated from Meta search engine outperformed existing search engines in terms of better retrieved search results with high precision.