TRIPTOUR:A Multi-itinerary Tourist Recommendation Engine Based on POI Visits Interval

Tourism is a vast industry in the world today and provides a country with a significant source of revenue and employment. Personalized multi-tour recommendations are challenging and time-consuming tasks. Recommended itineraries should fulfill tourists' desires and must be arranged within a limited time span. In addition, current multi-itinerary systems do not include Point Of Interest (POI) visit time in the suggested tour. The POI visit time vary according to the duration of the POI visit, e.g. longer duration of visits owing to the buying of tickets on the sot. To address these challenges, we use an algorithm named TRIPTOUR for suggesting multiple itineraries based on POI visit time, tourist attractions, popularity of itineraries, and the costs involved. The algorithm was developed to recommend itineraries for the visitors who want to visit unfamiliar locations. We also extracted related interface functionality from the Flickr dataset for the selection of different itineraries. The results demonstrate that the TRIPToUR approach outperforms the benchmark methods based on parameters such as precision, Recall, Fl-Score and the number of suggested itineraries.