TriPrec: Trip plan recommendation system that enhances hotel services
© 2017 Association for Computing Machinery. This paper presents a recommendation system for tourists who do not have a trip plan in a city they visit. Chiang Mai, Thailand is used as a case study. Thailand Department of Tourism's database and Foursquare API are used in our recommender system to...
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th-cmuir.6653943832-570582018-09-05T03:34:27Z TriPrec: Trip plan recommendation system that enhances hotel services Nonnadda Silamai Narongchai Khamchuen Santi Phithakkitnukoon Computer Science © 2017 Association for Computing Machinery. This paper presents a recommendation system for tourists who do not have a trip plan in a city they visit. Chiang Mai, Thailand is used as a case study. Thailand Department of Tourism's database and Foursquare API are used in our recommender system to create a one-day trip for the user. The recommendation is made based on the user's preferred tourist destination type images, current location, appropriate distance, time period, and place's popularity. The system also recommends restaurants and coffee shops that are nearby each recommended attraction, and it also displays the suggested route with street views so that the user can get an idea of how the journey is going to look like. Moreover, the user can print out the recommended result so that they can take it with them on their trip. The system is developed to be used as a desktop application installed at the hotel to enhance hotel services. 2018-09-05T03:34:27Z 2018-09-05T03:34:27Z 2017-09-11 Conference Proceeding 2-s2.0-85030870068 10.1145/3123024.3124414 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85030870068&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/57058 |
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Computer Science Nonnadda Silamai Narongchai Khamchuen Santi Phithakkitnukoon TriPrec: Trip plan recommendation system that enhances hotel services |
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© 2017 Association for Computing Machinery. This paper presents a recommendation system for tourists who do not have a trip plan in a city they visit. Chiang Mai, Thailand is used as a case study. Thailand Department of Tourism's database and Foursquare API are used in our recommender system to create a one-day trip for the user. The recommendation is made based on the user's preferred tourist destination type images, current location, appropriate distance, time period, and place's popularity. The system also recommends restaurants and coffee shops that are nearby each recommended attraction, and it also displays the suggested route with street views so that the user can get an idea of how the journey is going to look like. Moreover, the user can print out the recommended result so that they can take it with them on their trip. The system is developed to be used as a desktop application installed at the hotel to enhance hotel services. |
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Conference Proceeding |
author |
Nonnadda Silamai Narongchai Khamchuen Santi Phithakkitnukoon |
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Nonnadda Silamai Narongchai Khamchuen Santi Phithakkitnukoon |
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Nonnadda Silamai |
title |
TriPrec: Trip plan recommendation system that enhances hotel services |
title_short |
TriPrec: Trip plan recommendation system that enhances hotel services |
title_full |
TriPrec: Trip plan recommendation system that enhances hotel services |
title_fullStr |
TriPrec: Trip plan recommendation system that enhances hotel services |
title_full_unstemmed |
TriPrec: Trip plan recommendation system that enhances hotel services |
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triprec: trip plan recommendation system that enhances hotel services |
publishDate |
2018 |
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https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85030870068&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/57058 |
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