Tourism Management Studies

Trust-based Tourism Recommendation System Using Context-Aware Clustering

Document Type : Research Paper

Authors

AliAkbar Noorian 1
Reza Ravanmehr 2
Ali Harounabadi 2
Fatemeh Nouri 3

1 Ph.D. Student, Computer Engineering Department, Central Tehran Branch, Islamic Azad University, Iran

2 Assistant Professor, Computer Engineering Department, Central Tehran Branch, Islamic Azad University, Iran

3 M.Sc., Computer Engineering Department, Central Tehran Branch, Islamic Azad University, Iran

https://doi.org/10.22054/tms.2020.41870.2137
Abstract
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.

Keywords

Tourism recommendation system
Graph clustering
Context-aware
Trust
TripAdvisor
Tourism Management Studies
Volume 15, Issue 52
Autumn 2020
Pages 309-344

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