This paper mainly focuses on the personalization of the search engine based on data mining technique, such that user preferences are taken into consideration. Clickthrough data is applied on the user profile to mine the user preferences in order to extract the features to know in which users are really interested. The basic idea behind the concept is to construct the content and location ontology’s, where content represent the previous search records of the user and location refer to current location of user. SpyNB is the approach used to mining the user preferences from the Clickthrough data. The ranked support vector machine (RVSM) is performed on the searched results in order to display results according to user preferences by considering Clickthrough data.