Abstract: A recommender system plays a very vital role in recommending services to the users. The users here can rate their preferences and choose the services according to their requirements. The different recommendation services include services like books, hotels, newspapers, etc. The online information today is increasing on a large scale the data is growing rapidly, yielding the problem of big data to the environment. So, to overcome the problem of scalability on such big data problems, the recommendation systems have taken steps to overcome the same. In this study, the hotel recommendation system is considered. In most traditional recommendation systems, the distinct preferences of the users are not considered, i.e., the identical list of hotels is provided to every user without considering the users distinct preferences. For this reason in this study the reviews of distinct users are considered, so that, users with the identical tastes can be provided similar hotels list and users with distinct tastes with different hotels list.