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Context Trails: A Dataset to Study Contextual and Route Recommendation

P. Sánchez, A. Bellogín, J.L. Jorro-Aragoneses

19th ACM Conference on Recommender Systems - RecSys 2025, Praga (República Checa). 22-26 septiembre 2025


Resumen:

Recommender systems in the tourism domain are gaining increasing attention, yet the development of diverse recommendation tasks remains limited, largely due to the scarcity of public datasets. This paper introduces Context Trails, a novel dataset addressing this gap. Context Trails distinguishes itself by including not only user interactions with touristic venues, but also the itineraries (trails or routes) followed by users. Furthermore, it enriches existing item features (e.g., category, coordinates) with contextual attributes related to the interaction moment (e.g., weather) and the venue itself (e.g., opening hours). Beyond a detailed description of the dataset’s characteristics, we evaluate the performance of several baseline algorithms across three distinct recommendation tasks: classical recommendation, route recommendation, and contextual recommendation. We believe this dataset will foster further research and development of advanced recommender systems within the tourism domain. Dataset is available at https://zenodo.org/records/15855966; further code available at https://github.com/pablosanchezp/ContextTrailsExperiments.


Resumen divulgativo:

Presentamos Context Trails, un dataset turístico que enriquece con contexto (clima, horarios) las rutas seguidas por los usuarios visitando diferentes puntos de interés. Además, evaluamos un conjunto de  baselines en tres tareas: recomendación clásica, de rutas y  recomendación contextual.


Palabras clave: Dataset, Context, Tourism, Route recommendation, Evaluation


DOI: DOI icon https://doi.org/10.1145/3705328.3748151

Publicado en: RecSys '25: Proceedings of the Nineteenth ACM Conference on Recommender Systems, pp: 716-725, ISBN: 979-8-4007-1364-4

Fecha de publicación: 07-sep-2025


Cita:
P. Sánchez, A. Bellogín, J.L. Jorro-Aragoneses, "Context Trails: A Dataset to Study Contextual and Route Recommendation", presentado en 19th ACM Conference on Recommender Systems - RecSys 2025, Praga, República Checa, 22-26 septiembre 2025. En: RecSys '25: Proceedings of the Nineteenth ACM Conference on Recommender Systems, pp. 716-725, doi: 10.1145/3705328.3748151

    Líneas de investigación:
  • Machine Learning y Analítica Avanzada
    Grupos de investigación:
  • Instituto de Investigación Tecnológica (IIT)
    ODS:
  • Objetivo 11: Ciudades y comunidades sostenibles

IIT-25-306C_poster

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