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A survey on point-of-interest recommendations leveraging heterogeneous data

Author

Listed:
  • Zehui Wang

    (University of Applied Sciences Ravensburg-Weingarten)

  • Wolfram Höpken

    (University of Applied Sciences Ravensburg-Weingarten)

  • Dietmar Jannach

    (University of Klagenfurt)

Abstract

Tourism is an important application domain for recommender systems. In this domain, recommender systems are for example tasked with providing personalized recommendations for transportation, accommodation, points-of-interest (POIs), etc. Among these tasks, in particular the problem of recommending POIs that are of likely interest to individual tourists has gained growing attention in recent years. Providing POI recommendations to tourists can however be especially challenging due to the variability of the user’s context. With the rapid development of the Web and today’s multitude of online services, vast amounts of data from various sources have become available, and these heterogeneous data represent a huge potential to better address the challenges of POI recommendation problems. In this work, we provide a survey of published research on the problem of POI recommendation between 2021 and 2023. The literature was surveyed to identify the information types, techniques and evaluation methods employed. Based on the analysis, it was observed that the current research tends to focus on a relatively narrow range of information types and there is a significant potential in improving POI recommendation by leveraging heterogeneous data. As the first information-centric survey on POI recommendation research, this study serves as a reference for researchers aiming to develop increasingly accurate, personalized and context-aware POI recommender systems.

Suggested Citation

  • Zehui Wang & Wolfram Höpken & Dietmar Jannach, 2025. "A survey on point-of-interest recommendations leveraging heterogeneous data," Information Technology & Tourism, Springer, vol. 27(1), pages 29-73, March.
    • Handle: RePEc:spr:infott:v:27:y:2025:i:1:d:10.1007_s40558-024-00301-3
    DOI: 10.1007/s40558-024-00301-3
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    References listed on IDEAS

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    1. Deborah J. Mills & Lani Ramsey & Luis Furuya-Kanamori, 2021. "Pre- and Post-Travel Medical Consultations," Springer Books, in: Jeff Wilks & Donna Pendergast & Peter A. Leggat & Damian Morgan (ed.), Tourist Health, Safety and Wellbeing in the New Normal, pages 47-69, Springer.
    2. Wolfram Höpken & Matthias Fuchs, 2022. "Business Intelligence in Tourism," Springer Books, in: Zheng Xiang & Matthias Fuchs & Ulrike Gretzel & Wolfram Höpken (ed.), Handbook of e-Tourism, chapter 21, pages 497-527, Springer.
    3. Matthias Braunhofer & Francesco Ricci, 2017. "Selective contextual information acquisition in travel recommender systems," Information Technology & Tourism, Springer, vol. 17(1), pages 5-29, March.
    4. David Massimo & Francesco Ricci, 2021. "Popularity, novelty and relevance in point of interest recommendation: an experimental analysis," Information Technology & Tourism, Springer, vol. 23(4), pages 473-508, December.
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