Improvement in Ranking Relevancy of Retrieved Results from Google Search Using Feature Score Computation Algorithm

Abstract

Websites with a higher position in search engine ranking result; directly and positively affect visitors’ number to such sites. Search engine optimization (SEO) has become a promoting business that attempts to improve websites’ ranking. Sometimes, search engine results may contain undeserving websites at top rank due to SEO techniques in an unethical way. It misleads the search engine, and thereby it will increase the page rank of unfit websites. Due to this, such results downgrade the performance of search engines and frustrate the users. These irrelevant pages must be moved top-down from the search results to improve search engine quality. This paper analyzes Google results and proposes a novel approach to move down the top-ranking irrelevant Google search engine results. A ‘feature Score computation’ algorithm was presented here to compute scores based on features found in pages, and using the score, the pages are re-ranked to move down irrelevant results and uplift the relevant products. The accuracy of the corpus results’ relevancy was 88%, and after applying the algorithm, it was improved to 99%. This work improved the ranking of relevant products efficiently.