Location-Aware Personalized Traveler Recommender System (LAPTA) Using Collaborative Filtering KNN

Many tourists who travel to explore different cultures and cities worldwide aim find the best tourist sites, accommodation, food according their interests. This objective makes it harder for decide plan where go what do. Aside from hiring a local guide, an option which is beyond most travelers’ budgets, majority of sojourners nowadays use mobile devices search or recommend interesting sites on basis user reviews. Therefore, this work utilizes prevalent recommender systems app technologies overcome issue. Accordingly, study proposes location-aware personalized traveler assistance (LAPTA), system integrates preferences global positioning (GPS) generate recommendations. That integration will enable enhanced recommendation developed scheme relative those traditional used in customer ratings. Specifically, LAPTA separates data obtained Google locations into name category tags. After separation, fetches keywords user’s input past research behavior. The proposed uses K-Nearest algorithm match tags with suggestions. also provides suggestions nearby popular attractions using point interest feature enhance usability. experimental results showed that could provide more reliable accurate recommendations compared reviewed applications.