research-article

TripRec: trip plan recommendation system that enhances hotel services

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Santi PhithakkitnukoonAuthors Info & Claims

UbiComp '17: Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers

Pages 412 - 420

https://doi.org/10.1145/3123024.3124414

Published: 11 September 2017 Publication History

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Abstract

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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Cited By

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Chen TWu HHsu K(2024)Recommending suitable hotels to travelers in the post-COVID-19 pandemic using a novel FAHP-fuzzy TOPSIS approachComplex & Intelligent Systems10.1007/s40747-024-01521-010:5(6901-6915)Online publication date: 27-Jun-2024
https://doi.org/10.1007/s40747-024-01521-0
Toly Chen TWu HHsu K(2022)A fuzzy analytic hierarchy process-enhanced fuzzy geometric mean-fuzzy technique for order preference by similarity to ideal solution approach for suitable hotel recommendation amid the COVID-19 pandemicDIGITAL HEALTH10.1177/205520762210844578(205520762210844)Online publication date: 9-Mar-2022
https://doi.org/10.1177/20552076221084457
Deng ZWeng DWu Y(2022)You are experienced: interactive tour planning with crowdsourcing tour data from webJournal of Visualization10.1007/s12650-022-00884-126:2(385-401)Online publication date: 26-Oct-2022
https://dl.acm.org/doi/10.1007/s12650-022-00884-1
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Index Terms

TripRec: trip plan recommendation system that enhances hotel services
1. Human-centered computing

Recommendations

Hybrid group recommendations for a travel service

Recommendation techniques have proven their usefulness as a tool to cope with the information overload problem in many classical domains such as movies, books, and music. Additional challenges for recommender systems emerge in the domain of tourism such ...
Social group recommendation in the tourism domain

Recommender Systems learn users' preferences and tastes in different domains to suggest potentially interesting items to users. Group Recommender Systems generate recommendations that intend to satisfy a group of users as a whole, instead of individual ...
TripRec: recommending trip routes from large scale check-in data
WWW '12 Companion: Proceedings of the 21st International Conference on World Wide Web

With location-based services, such as Foursquare and Gowalla, users can easily perform check-in actions anywhere and anytime. Such check-in data not only enables personal geospatial journeys but also serves as a fine-grained source for trip planning. In ...

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Published In

UbiComp '17: Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers

September 2017

1089 pages

ISBN:9781450351904

DOI:10.1145/3123024

General Chairs:
Seungyon "Claire" Lee
Google
,
Leila Takayama
UC Santa Cruz
,
Khai Truong
University of Toronto

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 September 2017

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UbiComp '17

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UbiComp '17: The 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing

September 11 - 15, 2017

Hawaii, Maui

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Overall Acceptance Rate 764 of 2,912 submissions, 26%

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Cited By

View all

Chen TWu HHsu K(2024)Recommending suitable hotels to travelers in the post-COVID-19 pandemic using a novel FAHP-fuzzy TOPSIS approachComplex & Intelligent Systems10.1007/s40747-024-01521-010:5(6901-6915)Online publication date: 27-Jun-2024
https://doi.org/10.1007/s40747-024-01521-0
Toly Chen TWu HHsu K(2022)A fuzzy analytic hierarchy process-enhanced fuzzy geometric mean-fuzzy technique for order preference by similarity to ideal solution approach for suitable hotel recommendation amid the COVID-19 pandemicDIGITAL HEALTH10.1177/205520762210844578(205520762210844)Online publication date: 9-Mar-2022
https://doi.org/10.1177/20552076221084457
Deng ZWeng DWu Y(2022)You are experienced: interactive tour planning with crowdsourcing tour data from webJournal of Visualization10.1007/s12650-022-00884-126:2(385-401)Online publication date: 26-Oct-2022
https://dl.acm.org/doi/10.1007/s12650-022-00884-1
Kim TGoyal NKim JKim JHong S(2021)Supporting Collaborative Sequencing of Small Groups through Visual AwarenessProceedings of the ACM on Human-Computer Interaction10.1145/34492505:CSCW1(1-29)Online publication date: 22-Apr-2021
https://dl.acm.org/doi/10.1145/3449250
Kim THong SGoyal NKim JKim JBernhaupt RMueller FVerweij DAndres JMcGrenere JCockburn AAvellino IGoguey ABjørn PZhao SSamson BKocielnik R(2020)Consensus Building in Collaborative Sequencing with Visual AwarenessExtended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3334480.3382906(1-9)Online publication date: 25-Apr-2020
https://dl.acm.org/doi/10.1145/3334480.3382906
Stavrakis MKoutsabasis PGavalas DVosinakis S(2020)TouristHub: User Experience and Interaction Design for Supporting Tourist Trip Planning2020 IEEE 10th International Conference on Intelligent Systems (IS)10.1109/IS48319.2020.9199939(370-379)Online publication date: Aug-2020
https://doi.org/10.1109/IS48319.2020.9199939
Garcia LAciar SMendoza RPuello J(2018)Smart Tourism Platform Based on Microservice Architecture and Recommender ServicesMobile Web and Intelligent Information Systems10.1007/978-3-319-97163-6_14(167-180)Online publication date: 14-Jul-2018
https://doi.org/10.1007/978-3-319-97163-6_14

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Index Terms

Recommendations

Hybrid group recommendations for a travel service

Social group recommendation in the tourism domain

TripRec: recommending trip routes from large scale check-in data