Comprehensive Analysis of Personalized Web Search Engines Through Information Retrieval Feedback System and User Profiling

Abstract

Information retrieval with its feedback feature provides the way to bridge gap between user’s search queries and the documents returned by search engines. Recently, there has been a drift of personalization in Web search by many commercial and prominent search engines, where users receive different search results without considering relevancy of search query. Though many of the search engines are facilitating the features of personalized search results to provide the best user experiences of their search context. This paper provides composite review of research done for the personalization the web search as well as notified efforts has been done by web search engines to provide personalized results to users without compromising their privacy of search queries. Through the comparative analysis it has been identified the performance of key parameters like accuracy, efficiency and diversity of retrieved search result w.r.t. various user profiling and retrieval model techniques.