Design and Development of a Tourism Recommender System using Volunteered Geographic Information, Case Study: Yazd

Extended Abstract
Introduction
Tourism has positive economic, social, and cultural effects on human societies and is one of the most valuable sources of income in many countries. Travel planning is one of the most important issues that can be considered in order to have a good and desirable trip. Travel recommendation systems are examples of techniques used in the field of tourism that aim to match the characteristics of tourism resources or tourist attractions with the needs and priorities of tourists and provide the most appropriate tourism place. Voluntary geographic information (VGI) can play an important role in this regard. People in the community can monitor and share the geographic information of their environment as active, analytical, intelligent, responsible, environment-aware, circulate, distributed and interactive sensors.
This study recommends a system that intelligently receives demographic information, users' interests and preferences, and according to the spatial information shared as a VGI by other tourists, recommends the most suitable tourist attractions to the visitors using the recommendation system based on Bayesian networks. Also, the tourism-oriented GIS system, using the TSP algorithm, provides the most optimal route to reach the tourist attractions on the map.
 
Methodology
The study area is the historical area of ​​Yazd with an approximate area of ​​3.5 square kilometers, which is located in the city center. Yazd city, with an area of ​​107.4 square kilometers, is the largest historical unit and administrative center of Yazd province, which in recent years has faced a very large population growth compared to other urban areas of Yazd province.
In this research, the database of Yazd Municipality has been used to collect statistical information on tourism visits in 2015, the vector layer of the regional road network and the vector layers related to the location of tourist places, services and all related facilities. Also, in order to implement the tourism recommender system with a suitable user interface, software programs such as Arc GIS 10.5, PostgreSQL 9.6.1, Visual Studio 2013, NETICA 6.3, Notepad ++, and Geo-Server 2.13.2 have been exerted.
Bayesian network is one of the methods of presenting knowledge by combining Bayesian theory with a graphical model and has many applications in problem-solving and cause and effect analysis. This method uses a posterior probability distribution to analyze various parameters and includes a set of nodes and directional edges that nodes represent variables and edges represent cause and effect relationships between variables.
The Bayesian network designed in this study has been qualified and quantified based on demographic information (age, gender, income, occupation, level of education and type of travel of users), interests and preferences of tourists, and previous knowledge (information collected from related sources) in the NETICA software.
VGI is an essential source of geographic information when data collected from other sources is impossible. The information system designed in this research has a system to enter the preferences and interests of tourists after visiting tourist attractions. In this system, the experience of others is considered more than the experience of new people.
In addition to providing a list of tourist destinations tailored to users' preferences, a tourism recommender system also identifies the best route to access each tourist attraction. The routes suggested in this study start by moving from a tourist residence or hotel and return to the starting point after visiting the recommended places. For this reason, the TSP problem has been used for optimal routing in this system.
 
Results and discussion
This article aims to develop a tourism recommender system to offer suitable tourist attractions to tourists. The system can predict tourist attractions tailored to new users' interests and access paths based on combining the demographic information of new users with data from previous ones who voluntarily share their views of tourist attractions by composing recommendation algorithms and VGI data in the form of a Web-GIS system.
After introducing the tourist attractions, the user's movement route between the tourist attractions is done by specifying the starting point (Mehr Hotel). Also, in order to move the user, the suggested locations are extracted and the optimal route introduced by the system is displayed on the OSM map with the help of the network layer of the area roads. At any time, the user can view the nearest facilities on the map, such as coffee shops, restaurants, gas stations, hospitals, etc.
 
Conclusion
Determining the appropriate tourist attractions according to the interests and preferences of tourists is one of the important measures in tourism planning. Tourists will be delighted with a trip when their needs, interests, preferences, demographics, and social conditions are considered in the travel planning. In this research, a GIS web-based tourism recommender system has been created using voluntary geographic information and tourist demographic information. The system uses Bayesian network modeling to analyze the preferences of tourists and can predict the behavior of visiting tourist attractions through conditional probabilities and display the impact of each parameter and factor in selecting the type of tourist attractions. One of the most important features of this system is the possibility of user interaction so that tourists can voluntarily share their opinions and suggestions about the visited attractions. So, the system will provide recommendations related to tourist attractions that are in accordance with the interests and preferences of new tourists.