Hotel Recommendation System

Hotel recommendation systems aim to personalize travel experiences by suggesting accommodations tailored to individual preferences. Current research emphasizes leveraging user reviews through natural language processing techniques, like BERT, to understand guest sentiments and preferences, and incorporating user and item features within low-rank dynamic assortment models for efficient real-time recommendations. Furthermore, integrating large language models such as ChatGPT with persuasive technologies enhances the personalization and effectiveness of these systems, impacting user engagement and hotel revenue. These advancements improve the accuracy and efficiency of recommendations, ultimately enhancing the guest experience and optimizing hotel operations.