# Personalized Augmented Reality Based Tourism System: Big Data and User Demographic Contexts
## 8 Conclusions  
In this study, the concepts of a tour guide system in the GIS, which enriches the AR data by using the big spatial data, and the studies in this area are researched. In this research, a context-aware model to promote the AR-based tourism program was introduced and evaluated in order to develop a personalized AR based tour guide system. This system uses the time, position, score, age, and gender contexts to manage the high volume of data by using the VIKOR-SWARA method in order to combine these contexts and rank the tourist places that are suggested to the user. The results of this study are reviewed in two parts: evaluation of the machine learning results and the system evaluation. In the machine learning part, the results show better and more accurate performance with the DT than the SVM. In the studies that were conducted, the root mean square error for the DT is 0.287 and 0.361 for the SVM. In addition, the correct classified items for the DT were calculated to be 77.5% in this study, which used the percentage criterion. For the SMV, it was calculated to be 73.75%. In the case of the absolute mean error, the DT again had better accuracy (0.164) than the SVM (0.285). Another criterion that was considered to evaluate these two methods was the precision-recall chart. In this criterion, the DT diagram was also completely above the SVMDe diagram, which indicated better performance of the DT. Another indicator studied in this section was the classification error matrix, which was the overall accuracy criterion used to accurately study the table. The indicator rate for the DT was 77% and 73% for the SVM method. With the general evaluation of the system, the first users' opinions were studied using the statistical indicators. The first criterion had a standard deviation of 19, which the calculated standard deviation values show a small difference between the values of this evaluation and the average of the numbers. The highest amount for the standard deviation was related to question 9, which had a value of 0.844, and the lowest value was related to question 7, which was 0.568. This question had the highest level for the user's satisfaction regarding the ease-of-use, which can be due to the high attractiveness of the AR for the users. The next criteria are the lower quartile, the middle quartile, the upper quartile, and the interquartile range. With the evaluation of these four criteria, it was determined that the lower quartile and the middle quartile for all the questions is 4, and the upper quartile is 5, which leads the value of the interquartile range for all the questions to be 1. This indicates that the answers are close for all of the users, and it also shows their high satisfaction level. The next criterion was the data skewness. By studying and calculating this criterion, it was found that the data skewness was negative, and its amount was between -0.6 and -0.9, which indicates that the volume and the concentration of more data on the right, illustrating the users' high satisfaction level. The highest amount of skewness was related to question 3 and 7. In addition, by evaluating the ease-of-use and the usefulness of the system, these two questions had the highest user satisfaction, which generally indicates the high data density in the high numbers, which is high user satisfaction. The last criterion is studying the ease-of-use and the usefulness of the system. By studying these two criteria, it was found that the overall satisfaction of the users in terms of the ease-of-use was 55%, which was the highest amount and related to the simple receipt of information, which had a satisfaction rate of 60%. From the point of view of the usefulness of the system, the overall satisfaction of the tourists evaluated was 56%, and the highest value of this criterion was related to the attractiveness of the information display in the form of the AR, which had a 60% satisfaction rate. The study of these two criteria shows the desired level of the user's satisfaction with this system. Conceptualization, S.R.