Record link: 
http://hdl.handle.net/20.500.12708/225645
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Title: 
Workshop on Recommenders in Tourism (RecTour) 2025
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Citation: 
Neidhardt, J., Kuflik, T., Livne, A., Zanker, M., & Wörndl, W. (2025). Workshop on Recommenders in Tourism (RecTour) 2025. In RecSys ’25: Proceedings of the Nineteenth ACM Conference on Recommender Systems (pp. 1412–1413). Association for Computing Machinery. https://doi.org/10.1145/3705328.3748500
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Publisher DOI: 
10.1145/3705328.3748500
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Publication Type: 
Inproceedings - Full-Paper Contribution
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Language: 
English
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Authors: 
Neidhardt, Julia 
Kuflik, Tsvi 
Livne, Amit 
Zanker, Markus 
Wörndl, Wolfgang 
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Organisational Unit: 
E194-04 - Forschungsbereich Data Science 
E056-23 - Fachbereich Innovative Combinations and Applications of AI and ML (iCAIML) 
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Published in: 
RecSys '25: Proceedings of the Nineteenth ACM Conference on Recommender Systems 
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ISBN: 
979-8-4007-1364-4
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DOI of the book: 
10.1145/3705328
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Date (published): 
7-Sep-2025
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Event name: 
19th ACM Conference on Recommender Systems (RecSys '25) 
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Event date: 
22-Sep-2025 - 26-Sep-2025
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Event place: 
Prag, Czechia
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Number of Pages: 
2
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Publisher: 
Association for Computing Machinery, New York, NY, USA
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Peer reviewed: 
Yes
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Keywords: 
datasets; evaluation of tourism recommenders; LLMs in tourism; next-POI recommendations; Tourism recommenders
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Abstract: 
The Workshop on Recommenders in Tourism (RecTour) has been successfully held in conjunction with the ACM Conference on Recommender Systems (RecSys) since 2016, with the exception of one year. This workshop focuses on the unique and evolving challenges of recommender systems in the tourism domain. Over time, RecTour has fostered an active community supported by both academia and industry. In this overview paper, we outline our motivations for organizing the RecTour workshop and highlight the main topics covered in RecTour submissions, including destination recommendation, privacy concerns in travel recommender systems, the cold-start problem, transformer-based approaches in recommendation systems, and best practices for evaluation and experimentation.
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Project title: 
Christian Doppler Labor für Weiterentwicklung des State-of-the-Art von Recommender-Systemen in mehreren Domänen: CDL Neidhardt (Christian Doppler Forschungsgesells) 
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Research Areas: 
Information Systems Engineering: 100%
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Science Branch: 
1020 - Informatik: 90%
5020 - Wirtschaftswissenschaften: 10%
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Appears in Collections:
Conference Paper

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