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.

中文翻译：

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使用人工蜂群算法和模糊 TOPSIS 模型的游客酒店推荐系统：TripAdvisor 的案例研究

推荐系统在游客的决策过程中扮演着不可或缺的角色。对于游客来说，一个重要的问题是根据他们心目中的标准选择住宿，这可能同时包括几个项目。本文提出了一种旅游行业推荐系统的新方法，它结合了人工蜂群（ABC）算法和模糊 TOPSIS 模型。采用与理想解相似度排序技术（TOPSIS）是一种多准则决策方法，已被用于优化系统。本研究中提出的解决方案包括两个主要部分，其中采用的 ABC 算法得到了改进，并且比标准版本更有效。本研究针对 TripAdvisor 数据集，并根据真实数据提出了一种基于用户偏好的酒店推荐方法。获得的结果证明了研究中提出的方法的高精度。