2026-10-17T11:47:46Z https://meral.edu.mm/oai

oai:meral.edu.mm:recid/3272 2022-03-24T23:15:38Z 1582963302567:1597824273898 user-ucsy

Mobile Hybrid Recommendation System in Tourism Win, Nan Su Yee Tun, Myint Thu Zar Mobile phones are becoming a primaryplatform for information access and when coupledwith recommender system technologies, they canbecome key tools for mobile users to use bothleisure and business applications. In thispaper,this system is built upon the integration ofassociation rules mining and the collaborativefiltering approach as mobile hybridrecommendation system in tourism. Also, itprovides a hybrid framework recommendationsystem to be distinguishing Favorite and Non-Favorite places. For Favorite places, theframework straightly applies Adjusted CosineSimilarity method based on the generatedassociation rules to offer recommendations for theuser; for Non-favorite places, the frameworkapplies Jaccard Coefficient Method to offerrecommendations. Mean Absolute Error (MAE) isevaluated the accuracy of this mobile hybridrecommendation system 2017-12-27 http://hdl.handle.net/20.500.12678/0000003272 https://meral.edu.mm/records/3272