A Comprehensive Review of Hotel Recommendation Systems Using Reviews and AI

Authors

  • Patel Diya Department of Computer Engineering (Software Engineering), Ipcowala Institute of Engineering & Technology, Dharmaj,Gujarat Technological University, Gujarat, India Author
  • Dr. Padiya Swity R Professor, Department of Computer Engineering, Ipcowala Institute of Engineering & Technology, Dharmaj, Gujarat Technological University, Gujarat, India Author
  • Prof. Patel Ketankumar Assistant Professor, Department of Computer Engineering, Ipcowala Institute of Engineering & Technology, Dharmaj, Gujarat Technological University, Gujarat, India Author

DOI:

https://doi.org/10.32628/CSEIT261215

Keywords:

Hotel Recommendation, Sentiment Analysis, Deep Learning, Tourism Analytics, Recommender Systems

Abstract

Hotel recommendation systems have become a vital component of modern tourism platforms due to the exponential growth of online hotel reviews and user-generated content. These systems assist travelers in making informed booking decisions by analyzing customer preferences, sentiments, and contextual factors. Recent advances in artificial intelligence, machine learning, and deep learning have significantly improved recommendation accuracy, personalization, and scalability. This review paper presents a comprehensive analysis of state-of-the-art hotel recommendation approaches published between 2024 and 2025, with particular emphasis on sentiment analysis, hybrid recommender models, deep learning architecture, and explainable AI techniques. The study systematically examines methodological trends, advantages, and limitations across existing works, highlighting how textual reviews, metadata, and contextual information are integrated into recommendation pipelines. Furthermore, this review identifies key research findings and challenges related to data sparsity, ambiguity in natural language, fairness, explainability, and ethical considerations. By synthesizing recent research contributions, this paper aims to provide a structured understanding of current progress and future research directions in hotel recommendation systems, offering valuable insights for researchers and practitioners working in intelligent tourism and hospitality analytics.

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Published

10-01-2026

Issue

Vol. 12 No. 1 (2026): January-February

Section

Research Articles

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Copyright (c) 2026 International Journal of Scientific Research in Computer Science, Engineering and Information Technology

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Patel Diya, Dr. Padiya Swity R, and Prof. Patel Ketankumar, “A Comprehensive Review of Hotel Recommendation Systems Using Reviews and AI”, Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol, vol. 12, no. 1, pp. 115–120, Jan. 2026, doi: 10.32628/CSEIT261215.