Personalization of Search Engines, Based-on Comparative Analysis of User Behavior

In this research work, the impact of user’s behavior on search engine results is discussed. It aims to improvement of search results which leads to the higher satisfaction of users. In other words, we are trying to present a personalized search engine for each user, based on his/her activity and search history. We base our hypothesis that the search history of each user in a specific time frame provides precious information to be used in case of offering customizable and more efficient results to the user. In order to evaluate our research project hypothesis, we designed and implemented an experimental search engine as a web platform. This search engine measures the level of user’s satisfaction by bringing putting extra information into account. According to the experimental results, consideration of the user’s behavior history has significant effect on the quality of the search results, leading to more satisfaction of the users.