A Novel Tour Planning Model using Big Data

Nowadays, many people travel around the world to visit attractions places which have tremendous economic impact on the countries. Tour planning is one of the most beneficial areas in tourism, but the production of tourism tools and tour planning process are not easy tasks. The purpose of the tour planning tools is to increase the satisfaction of tourists, which is provided with a high number of visits and reduced time between visits and travel costs. In this paper, a novel model is proposed for tour planning based on user demands and considering important parameters such as tour cost, traffic volume, weather and time of tour in the city of tourist destination. This model generates various tour plans using big data which comprise traffic data, weather data, events data, tourism data and tourist profile. It offers the best plan according to user priorities and constraints. The main purpose of this model is to select the points of interest by the user, and to arrange the visits based on the knowledge obtained from the big data of the tour planning.