A Comparative Study of Algorithms in SEO & Approach for Optimizing the Search Engine Results Using Hybrid of Query Recommendation and Document Clustering, Genetic Algorithm

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Provided by: International Journal of Computing Science and Information Technology (IJCSIT)
Topic: Big Data
Format: PDF
Promoting a website in search engine result is a major task for a webmaster and SEO engineer in website development. This paper become bottleneck for Webmaster or Search Engine Optimization (SEO) engineer to drive visitors to their site by learning technique and algorithm. In this paper, the authors present a comparative study of various algorithms use by search engine like page rank algorithm, weighted page rank algorithm, HITS algorithm, query independent algorithm and proposed an hybrid approach for optimizing the search engine results using artificial intelligence techniques such as document clustering, genetic algorithm and query recommendation to provide the user with the most relevant pages to the search query.
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