# Personalized Augmented Reality Based Tourism System: Big Data and User Demographic Contexts
## 4 Methodology
### Place Type Prediction  
The first step of designing the personalized AR tourist system is to predict the type of tourist places where the user's interests are according to the user's demographic information. A machine learning method is used to do this in order to classify the tourist types by reflecting the user's interests. This method is conducted in order to achieve the associations between the place ranking and the demographic contexts. In the classification process, the place rate is considered in order to obtain what places the user is interested in visiting, which is based on the demographic contexts, in addition to the place type. For each user, the tourist places are classified into two classes, which include the favorite places and the unfavorite places, according to their ratings of the touristic places. After the normalizing the ranks of places between 0 and 10, if the rank of one place is less than 7, it is considered as the unfavorite, otherwise it is the favorite place. Figure 2 shows the place type classification used in this research. Figure 1: General implementation method. Figure 2: Place type classification according to the user’s interests. In order to classify the tourist places to reflect the user's interests and preferences, the demographic context is considered, which includes gender, age, and level of education. It is clear that people who visit an attractive place often have similar interests and preferences. Studies [13; 15; 42; 43; 44; 45; 46; 47; 48] confirmed that the age and gender of a tourist is effective with tourism. These studies have also shown that the level of education of the individuals is important concerning the type of tourist activities they engage in. In order to visualize the most suitable places through an AR camera, we predicted the place types that the user is interested in by classifying similar users with similar demographic contexts. The types of tourist places that a tourist may visit are shown in Figure 3. In this figure, the tourist places are divided into eight main categories, which include residence, art and theater, entertainment and sports, restaurants and fast foods, green areas, natural attractions, religious attractions, and historical and cultural attractions. Each category contains several types of tourist places. For each place, two parameters are considered, which include the service time and service type, in addition to the spatial information. The service time is the length of time that the place is open and provides services to the users. The tourist places have different service times depending on their use. In addition, when a tourist is using tourism systems, they expect places that are out-of-service to have times that are not offered. Table 1 shows the service time of some tourist places in Tehran. Some places provide services to a specific gender, so the service type has one of these values: men services, women services, or none. For example, in Tehran, there are some places that provide services only to women, such as women's parks, swimming pools, and water parks. Figure 3: The tourist place categories. Place Type Filtering  
Ranking the touristic places according to the user's demographics, location, and time context is conducted in two steps. The function and the duty of the time filter in this system are to remove the places that are out-of-service time from the user's suggestions. For this purpose, a time filter is applied to the output that was obtained from the previous step. When collecting the information, the service time for each type of tourist place is also collected and stored in a database. Some examples are given in Table 1.  
After checking the service time and matching it with the user's request time, the user's position is checked. As previously mentioned, the latitude and longitude for locations of the tourist places are stored in the database. When the user submits his or her request, the latitude and longitude position of the user is taken by the system and checked on the server side around the user.