An Effective Hotel Recommendation System through Processing Heterogeneous Data

Recommendation systems have recently gained a lot of popularity in various industries such as entertainment and tourism. They can act filters information by providing relevant suggestions to the users through processing heterogeneous data from different networks. Many travelers tourists routinely rely on textual reviews, numerical ratings, points interest select hotels cities worldwide. To attract more customers, online hotel booking typically rank their based recommendations customers. In this paper, we present framework that analyzing hotels’ customer reviews nearby amenities. addition, is presented combines scores generated user surrounding facilities. We perform experiments using datasets platforms TripAdvisor Booking evaluate effectiveness applicability proposed framework. first store keywords extracted assign weights each considered unigram bigram and, then, give score keyword. Finally, our system aggregates environments categories Experimental results confirm recommendation