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Web page rank estimation in search engine based on SEO parameters using machine learning techniques


Hengameh Banaei and Ali Reza Honarvar


Vol. 17  No. 5  pp. 95-100


E-Commerce is growing day by day so that most of the requirements of customers can easily be provided through websites. In such conditions, the Web markets to stay on competition needs one of two methods of advertising and increasing site rank in search engine results.This research wants to analysis website’s internal parameters that affect determining site rank in Google's search engine. Forasmuch as how to choose and number of HTML tags for a particular website has direct impact on page rank, important concepts in this area should be examined. These concepts includs Number, Proximity and Density. For extract required data for this research we design a crawler and parser. Then dataset has been learning by ANN. Then, this ANN is used to predict new websites rank that has good performance on test data.


Search Engine Optimization, E-Commerce, Site Rank, Artificial Neural Network