How to Improve Your Google Ranking: Myths and Reality

Abstract

Abstract-Search engines have greatly influenced the way people access information on the Internet as such engines provide the preferred entry point to billions of pages on the Web. Therefore, highly ranked web pages generally have higher visibility to people and pushing the ranking higher has become the top priority for webmasters. As a matter of fact, search engine optimization (SEO) has became a sizeable business that attempts to improve their clients' ranking. Still, the natural reluctance of search engine companies to reveal their internal mechanisms and the lack of ways to validate SEO's methods have created numerous myths and fallacies associated with ranking algorithms; Google's in particular.In this paper, we focus on the Google ranking algorithm and design, implement, and evaluate a ranking system to systematically validate assumptions others have made about this popular ranking algorithm. We demonstrate that linear learning models, coupled with a recursive partitioning ranking scheme, are capable of reverse engineering Google's ranking algorithm with high accuracy. As an example, we manage to correctly predict 7 out of the top 10 pages for 78% of evaluated keywords. Moreover, for content-only ranking, our system can correctly predict 9 or more pages out of the top 10 ones for 77% of search terms. We show how our ranking system can be used to reveal the relative importance of ranking features in Google's ranking function, provide guidelines for SEOs and webmasters to optimize their web pages, validate or disapprove new ranking features, and evaluate search engine ranking results for possible ranking bias.

Search Engine Optimization Techniques for Malaysian University Websites: A Comparative Analysis on Google and Bing Search Engine

“…Google considers this type of inbound link a vote of assurance. The underlying supposition is that most famous sites are expected to get more inbound links from other good sites [26]. Google PageRank is ranging from zero to 10, where 10 is the best and zero being the worst PageRank.…”

How to reverse-engineer quality rankings

“…The search engine optimization (SEO) industry aims to be able to boost the search engine rank of a web page by figuring out which features have high influence in the ranking algorithm. For instance, Su et al (2010) used a linear optimization model to approximate Google web page rankings. As a final example, Hammer et al (2007) approximated credit rating models using Logical Analysis of Data.…”

Web Page Recommendation System Using Laplace Correction Dependent Probability and Chronological Dragonfly-Based Clustering

“…The web mining was also referred to as data mining in the web and it allowed the user to get access to information available on the internet, data log in the internet providing the information about the services, and the structure of the web. Web mining identified the pattern/behavior of the user browsing through the internet platform [19] [4]. Various literature schemes have explored the WUM for improving the quality of the webpage recommendation schemes.…”