Mobile Hybrid Recommendation System in Tourism

Abstract

Mobile phones are becoming a primary platform for information access and when coupled with recommender system technologies, they can become key tools for mobile users to use both leisure and business applications. In this paper,this system is built upon the integration of association rules mining and the collaborative filtering approach as mobile hybrid recommendation system in tourism. Also, it provides a hybrid framework recommendation system to be distinguishing Favorite and Non- Favorite places. For Favorite places, the framework straightly applies Adjusted Cosine Similarity method based on the generated association rules to offer recommendations for the user; for Non-favorite places, the framework applies Jaccard Coefficient Method to offer recommendations. Mean Absolute Error (MAE) is evaluated the accuracy of this mobile hybrid recommendation system