Theoretical Fundamentals of Search Engine Optimization Based on Machine Learning

Abstract

The theoretical basis of search engine optimization (SEO) process, metrics of its efficiency and the algorithm of performance were proposed. It is based on the principles of situation control, machine learning, semantic net building, data mining and service oriented architecture as IT solution. The main idea of the scientific work is the use of situation control as a learning method for search engine to recognize WEB site content in the Internet. In this case built semantic net of WEB site content is a learning sample to teach search engine. To receive the keyword list (semantic kernel) of web content the modified algorithm of semantic net building was proposed. Developed service oriented IT solution includes PrestaShop CMS, 1C Enterprise component and WEB services done by Google and Yandex. An efficiency of the approach was proved by successful performance of 25 real SEO projects in 2012-2016 for the companies in Ukraine.