Hotel Recommendation System Based on Hybrid Recommendation Model
Hotel Recommendation System Based On Hybrid Recommendation Model software project report develops a hybrid model that combines content-based with collaborative filtering (CF) for hotel recommendation. This model considers both hotel popularity in input destination and users preference. It produces the prediction with 53.6% accuracy on test data-4% improvement on purely content-based model. Addtionally, three issues are well-resolved when implementing CF: sparsity in utility matrix, cold-start, and scalability. Student Free Project on Hotel Recommendation System Based on Hybrid Recommendation Model. Click here to get complete Software projects lists.
The goal of the project is to develop a hybrid model for better hotel recommendation. At this moment, the majority of the recommendation systems are content-based models, which only consider the searching paramaters input by customers but not the users preference. For instance, Expedia focuses on the searching criterion and recommends the top popular local hotels. Personalizing the user search by their preference is a burning need for better hotel recommendation. Collaborative filtering is considered as the starting point of this project. It has been widely used in recommendation systems but rarely in hotel recommendation. Nevertheless, there are still related works.
