Hotel Recommendation Based on Hybrid Model
نویسندگان
چکیده
This project 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.
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