A Group Travel Recommender System Based on Group Approximate Constraint Satisfaction

Abstract

In today’s travel landscape, there’s a growing demand for experiences that cater specifically to group travelers, whose needs often differ from those of solo travelers. Despite the abundance of information available on community sites like TripAdvisor, the extensive planning required can be time-consuming. This highlights the need for a recommendation system tailored to the nuances of group travel. Our study focuses on enhancing travel experiences for groups by proposing customized travel packages that take into account various preferences, such as destinations, budget constraints, and individual components like flights, hotels, and events. We introduce a method that combines Collaborative Filtering (CF) for destination recommendations with a group consensus decision-making process, factoring in individual preferences as constraints. This approach led to the creation of the GRec_Tr system, which not only suggests travel destinations but also offers comprehensive package recommendations, including flights, hotels, and activities. Our method aims to improve the overall travel experience, increase traveler satisfaction, and potentially boost sales for travel agencies. It also expands the scope of traditional CF-based systems by integrating diverse travel components into the recommendation process.

Keywords

• Approximate constraint satisfaction
• collaborative filtering
• group travel recommendation
• group satisfaction
• travel package