demonstration

Enhancing Travel Experience Leveraging on-line and off-line Users' Behaviour Data

Authors:

David Massimo,

Francesco RicciAuthors Info & Claims

IUI '20 Companion: Companion Proceedings of the 25th International Conference on Intelligent User Interfaces

Pages 65 - 66

https://doi.org/10.1145/3379336.3381466

Published: 17 March 2020 Publication History

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Abstract

Several tourism applications have been designed to support on-line information search and content browsing. However, often they neglect user's current visit experience, i.e., what the user already experienced off-line. In this demo we showcase a novel mobile app enhancing a traveller's visit experience by considering the visit context and the traveller's currently visited locations. The app has been designed as a tool for advancing the state of the art in decision support systems. The app can be used outside the lab, hence taking into account the true complexity of user decision making, while lab experiments tend to over-simplify that.

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Cited By

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Massimo DRicci F(2023)Combining Reinforcement Learning and Spatial Proximity Exploration for New User and New POI RecommendationsProceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization10.1145/3565472.3592966(164-174)Online publication date: 18-Jun-2023
https://dl.acm.org/doi/10.1145/3565472.3592966
Not E(2021)Mining mobile application usage data to understand travel planning for attending a large eventInformation Technology & Tourism10.1007/s40558-021-00204-723:3(291-325)Online publication date: 5-Jun-2021
https://doi.org/10.1007/s40558-021-00204-7
Massimo DRicci F(2021)Next-POI Recommendations Matching User’s Visit BehaviourInformation and Communication Technologies in Tourism 202110.1007/978-3-030-65785-7_4(45-57)Online publication date: 12-Jan-2021
https://doi.org/10.1007/978-3-030-65785-7_4

Index Terms

Enhancing Travel Experience Leveraging on-line and off-line Users' Behaviour Data
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Recommender systems

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Information

Published In

IUI '20 Companion: Companion Proceedings of the 25th International Conference on Intelligent User Interfaces

March 2020

153 pages

ISBN:9781450375139

DOI:10.1145/3379336

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 March 2020

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Demonstration
Research
Refereed limited

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IUI '20

Sponsor:

SIGAI
SIGCHI

IUI '20: 25th International Conference on Intelligent User Interfaces

March 17 - 20, 2020

Cagliari, Italy

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Overall Acceptance Rate 746 of 2,811 submissions, 27%

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IUI '25

Sponsor:
sigai
sigai

30th International Conference on Intelligent User Interfaces

March 24 - 27, 2025

Cagliari , Italy

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Cited By

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Massimo DRicci F(2023)Combining Reinforcement Learning and Spatial Proximity Exploration for New User and New POI RecommendationsProceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization10.1145/3565472.3592966(164-174)Online publication date: 18-Jun-2023
https://dl.acm.org/doi/10.1145/3565472.3592966
Not E(2021)Mining mobile application usage data to understand travel planning for attending a large eventInformation Technology & Tourism10.1007/s40558-021-00204-723:3(291-325)Online publication date: 5-Jun-2021
https://doi.org/10.1007/s40558-021-00204-7
Massimo DRicci F(2021)Next-POI Recommendations Matching User’s Visit BehaviourInformation and Communication Technologies in Tourism 202110.1007/978-3-030-65785-7_4(45-57)Online publication date: 12-Jan-2021
https://doi.org/10.1007/978-3-030-65785-7_4

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Recommendations

Tourism and Travel Electronic Commerce in China

Designing an immersive tour experience system for cultural tour sites

The travel machine: mobile UX design that combines information design with persuasion design