Trust-based Tourism Recommendation System Using Context-Aware Clustering

Nowadays, in the age of communication, the production and transmission of information are increasing rapidly. There are also many destinations in the tourism sector that are worth traveling, but increasing the number of suitable tourist destinations through the high volume of choices makes it harder to choose the desired option. Therefore, the prioritization and personalization of the information have become a necessity for providing appropriate and effective recommendation. In this paper, considering the target user's location, a tourist recommendation system is proposed to suggest a perfect place for tourist accommodation using context information, trust criteria and graph clustering to increase the accuracy of recommendations. The experiments and evaluations on TripAdvisor dataset show that the proposed method suggests better results than other state-of-the-art methods.