Developing a recommender system for the health tourism industry using data mining methods
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...
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University of Qom
2023-03-01
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| Series: | مدیریت مهندسی و رایانش نرم |
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| Online Access: | https://jemsc.qom.ac.ir/article_1848_8fd7e7689717af17804de4336efb45d4.pdf |
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| _version_ | 1832577580247547904 |
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| author | reza molaee fard |
| author_facet | reza molaee fard |
| author_sort | reza molaee fard |
| collection | DOAJ |
| description | 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 |
| format | Article |
| id | doaj-art-553ca2d39d364faca2efa219a2b85eea |
| institution | Kabale University |
| issn | 2538-6239 2538-2675 |
| language | fas |
| publishDate | 2023-03-01 |
| publisher | University of Qom |
| record_format | Article |
| series | مدیریت مهندسی و رایانش نرم |
| spelling | doaj-art-553ca2d39d364faca2efa219a2b85eea2025-01-30T20:18:25ZfasUniversity of Qomمدیریت مهندسی و رایانش نرم2538-62392538-26752023-03-01821251421848Developing a recommender system for the health tourism industry using data mining methodsreza molaee fard0Master of Computer-Software, Dezful Branch, Islamic Azad University, Dezful, Iran. Email: rezamolae4@gmail.comIn 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 correctlyhttps://jemsc.qom.ac.ir/article_1848_8fd7e7689717af17804de4336efb45d4.pdfrecommender systemhealth tourismdata mining web miningparticipatory filtering |
| spellingShingle | reza molaee fard Developing a recommender system for the health tourism industry using data mining methods مدیریت مهندسی و رایانش نرم recommender system health tourism data mining web mining participatory filtering |
| title | Developing a recommender system for the health tourism industry using data mining methods |
| title_full | Developing a recommender system for the health tourism industry using data mining methods |
| title_fullStr | Developing a recommender system for the health tourism industry using data mining methods |
| title_full_unstemmed | Developing a recommender system for the health tourism industry using data mining methods |
| title_short | Developing a recommender system for the health tourism industry using data mining methods |
| title_sort | developing a recommender system for the health tourism industry using data mining methods |
| topic | recommender system health tourism data mining web mining participatory filtering |
| url | https://jemsc.qom.ac.ir/article_1848_8fd7e7689717af17804de4336efb45d4.pdf |
| work_keys_str_mv | AT rezamolaeefard developingarecommendersystemforthehealthtourismindustryusingdataminingmethods |