A RECOMMENDATION MOBILE APPLICATION FOR TOURIST’S PERSONAL PREFERENCE BY MACHINE LEARNING

Natthapol  Chainongbua; Kanyarat  Bussaban; Kunynuth  Kularbphettong

Natthapol Chainongbua Faculty of Science and Technology, Suan Sunandha Rajabhat University, Bangkok, Thailand
Kanyarat Bussaban Faculty of Science and Technology, Suan Sunandha Rajabhat University, Bangkok, Thailand
Kunynuth Kularbphettong Faculty of Science and Technology, Suan Sunandha Rajabhat University, Bangkok, Thailand

Keywords: Recommendation system, Mobile application, Tourist’s Personal Preference, Machine Learning

Abstract

Nowadays, with the rapid growth of mobile technology, a mobile tourist recommendation system is widely applied tools for offering travel information. Tourists can access self-guided travel information through the internet. However, there is a lot of travel and tourism information. Therefore, this research aims to develop a recommendation mobile application for tourist’s personal preference by using Collaborative Filtering technique, which uses the principle of Cosine Similarity. Collaborative filtering is a significant technique widely used by recommender systems and it uses similarities between users and items to filter out items that a user might like. The evaluation of model accuracy was performed by comparing RMSE and MAE values. Also, the results indicate that the recommendation mobile application was achieved the objective to recommend tourist attractions based on users need.