This research proposes a new recommendation system for recommendation generation based on users' ratings and personal profiles. Motivated by existing studies, firstly we propose item-based collaborative filtering to recommend tourist spots based on users' rating. In addition, we incorporate the content-based filtering algorithm with Naïve Bayes Classifier, for recommendation generation. Detailed analysis of these proposed methods are discussed which will give a clear view on how the core part of the recommendation systems has been implemented. The proposed TRS was evaluated using several data sets to indicate its efficiency.
|Title of host publication||Proceedings of 2021 International Conference on Machine Learning and Cybernetics, ICMLC 2021|
|Publication status||Published - 2021|
|Event||20th International Conference on Machine Learning and Cybernetics, ICMLC 2021 - Adelaide, United States|
Duration: 4 Dec 2021 → 5 Dec 2021
|Name||Proceedings - International Conference on Machine Learning and Cybernetics|
|Conference||20th International Conference on Machine Learning and Cybernetics, ICMLC 2021|
|Period||4/12/21 → 5/12/21|