Master of Computer-Software, Dezful Branch, Islamic Azad University, Dezful, Iran. Email: rezamolae4@gmail.com
Abstract
In this research, a new method is presented to improve the recommendation systems in the field of health tourism, which can make accurate predictions by using participatory filtering and by using the points that previous tourists have given to places and health professionals in our country. For the use of tourists. According to the research, data clustering using DBSCAN algorithm obtained 99% efficiency score, which is the highest efficiency score among the existing algorithms. Also, SVM method has 95% score in accuracy section and 99% score in call section. Which shows the high accuracy of predicting the results and the proposed method in general up to 80% can correctly identify the places needed by the tourist and suggest the appropriate place to a large extent correctly
molaee fard, R. (2023). Developing a recommender system for the health tourism industry using data mining methods. Engineering Management and Soft Computing, 8(2), 125-142.
MLA
reza molaee fard. "Developing a recommender system for the health tourism industry using data mining methods". Engineering Management and Soft Computing, 8, 2, 2023, 125-142.
HARVARD
molaee fard, R. (2023). 'Developing a recommender system for the health tourism industry using data mining methods', Engineering Management and Soft Computing, 8(2), pp. 125-142.
VANCOUVER
molaee fard, R. Developing a recommender system for the health tourism industry using data mining methods. Engineering Management and Soft Computing, 2023; 8(2): 125-142.
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