Time is one of the important criteria which we have to consider in day-to-day life. Every one's passion is to retrieve the optimum data within a short span of time. In this paper we are observing the general time sensitive queries. Queries are also important along with finding topic similarity and final document ranking process. The proposal of this paper is to construct a general framework which will handles the time sensitive queries and also identifies sensitive time intervals for those queries. we construct BM25 techniques which will provides the overall ranking mechanism. We analyse extended experimental results with various news articles, TREC data and news archives. Finally we provide a conclusion that our techniques are more efficient and it significantly improves the quality results of time sensitive queries compared to the state-of-the-art retrieval techniques. © 2013 IEEE.