Giving Future Vision to IR: A Query Clustering Approach - Dubey, Gaurav; Nayak, Romina; Wadhwa, Neha; Rana, Ajay (International Journal of Computer Sciences and Engineering, 2014)
Information Retrieval (IR) has become very tedious given the amount of data handled these days. Search engines are posed with an ever increasing responsibility of giving precise responses to user queries in minimal time. In this paper, we present a query clustering approach which identifies Frequently Asked Questions (FAQs) for answering future queries. The proposed approach is based on identification of distinct subjects from queries enquired& logged in the past. The queries falling under each of the subject category are then reduced to a group which represents the frequently asked queries. In the past, these queries have been asked frequently & thus have an inclination of being repeated in the future. This will give the interface (e.g. search engines) an ability to predict future queries and respond in a time efficient manner. We extend this approach on a Real Estate data warehouse which proves its viability and efficiency in Real Estate domain as well.