A Hotel Recommender System for Tourists Using the Artificial Bee Colony Algorithm and Fuzzy TOPSIS Model: A Case Study of TripAdvisor

Saman Forouzandeh, Kamal Berahmand (), Elahe Nasiri () and Mehrdad Rostami ()
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Saman Forouzandeh: Department of Computer Engineering, University of Applied Science and Technology, Center of Tehran Municipality ICT org., Tehran, Iran
Kamal Berahmand: #x2020;Department of Science and Engineering, Queensland University of Technology, Brisbane, Australia
Elahe Nasiri: #x2021;Department of Information Technology and Communications, Azarbaijan Shahid Madani University, Tabriz, Iran
Mehrdad Rostami: #xA7;Department of Computer Engineering, University of Kurdistan, Sanandaj, Iran

International Journal of Information Technology & Decision Making (IJITDM), 2021, vol. 20, issue 01, 399-429

Abstract: Recommendation systems play an indispensable role in tourists’ decision-making process. An important issue for tourists concerns the selection of accommodation in accordance with the criteria on their minds, which may include several items at the same time. This paper proposes a novel approach to recommendation systems in the tourism industry involving a combination of the Artificial Bee Colony (ABC) algorithm and the fuzzy TOPSIS model. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), a multi-criteria decision-making method, has been utilized to optimize the system. The solution presented in this research includes two major parts, where the employed ABC algorithm has been improved and is more efficient than the standard version. This research has addressed the TripAdvisor dataset and presented a method for hotel recommendations based on user preferences according to real data. The obtained results demonstrate the high accuracy of the method presented in the research.

Keywords: Recommender system; artificial bee colony algorithm; TOPSIS model; trip advisor (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1142/S0219622020500522

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