Query disambiguation problem is getting more attention as the data available on the web grows exponentially. To address this problem, we present a system that extracts relevant categories as the user's intention in search. To predict the categories of a given user input query, we employed machine learning algorithms that learn the correlation between the query categories and the user search history.