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Nowadays, people start to use online reservation systems to plan theirvacations since they have vast amount of choices available. Selecting when andwhere to go from this large-scale options is getting harder. In addition,sometimes consumers can miss the better options due to the wealth ofinformation to be found on the online reservation systems. In this sense,personalized services such as recommender systems play a crucial role indecision making. Two traditional recommendation techniques are content-basedand collaborative filtering. While both methods have their advantages, theyalso have certain disadvantages, some of which can be solved by combining bothtechniques to improve the quality of the recommendation. The resulting systemis known as a hybrid recommender system. This paper presents a new hybrid hotelrecommendation system that has been developed by combining content-based andcollaborative filtering approaches that recommends customer the hotel they needand save them from time loss.

Hotel Recommendation System Based on User Profiles and Collaborative Filtering