PERSONALIZED RANKING FOR SEARCH ENGINES BASED ON WEB USAGE ANALYSIS Mohammad Suaib Author

The introduction of high-speed internet and the rise in smart phone internet users has resulted in an unfathomable surge of internet data on the Web. Because there is no centralized monitoring of data to be kept, indexed, and retrieved on the web, Search Engines are faced with a difficult task of retrieving searched information from the Web not only in a timely manner, but also to the exact and near accuracy of user interest and intent. As a result of the exponential growth in the number of digital data on the web, Web Search Engines must be clever and capable of obtaining the requested information based on the needs and preferences of internet users. For this purpose, ranking web pages becomes an important task for the fact that it helps users in finding highly rated web-pages that are believed to be the most relevant to their intended search. But this task is not a simple task as it requires to infer and figure out the interest and intent of the user making search thereon web. To apprehend the user’s interest in order to rank the web-pages several metrics have been proposed by the researchers wherein ranking directly corresponds to the quality and relevance of web-pages explored during the search (Micarelli et al., 2007). Taking this objective forward, a search engine needs to be developed which can take up the user’s queries in the most understanding manner and then successfully optimize the ranking of online webpages according to the user’s requirements using web usage data (Bao et al., 2007).