Record link: 
http://hdl.handle.net/20.500.12708/224590
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Title: 
LongEval at CLEF 2025: Longitudinal Evaluation of IR Systems on Web and Scientific Data
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Citation: 
Cancellieri, M., El-Ebshihy, A., Fink, T., Fröbe, M., Galuščáková, P., Gonzalez-Saez, G., Goeuriot, L., Iommi, D., Keller, J., Knoth, P., Mulhem, P., Piroi, F., Pride, D., & Schaer, P. (2026). LongEval at CLEF 2025: Longitudinal Evaluation of IR Systems on Web and Scientific Data. In J. Carrillo-de-Albornoz, A. García Seco de Herrera, J. Gonzalo, L. Plaza, J. Mothe, F. Piroi, P. Rosso, D. Spina, G. Faggioli, & N. Ferro (Eds.), Experimental IR Meets Multilinguality, Multimodality, and Interaction : 16th International Conference of the CLEF Association, CLEF 2025, Madrid, Spain, September 9–12, 2025, Proceedings (pp. 363–387). Springer. https://doi.org/10.1007/978-3-032-04354-2_20
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Publisher DOI: 
10.1007/978-3-032-04354-2_20
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Publication Type: 
Inproceedings - Full-Paper Contribution
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Language: 
English
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Authors: 
Cancellieri, Matteo 
El-Ebshihy, Alaa 
Fink, Tobias 
Fröbe, Maik 
Galuščáková, Petra 
Gonzalez-Saez, Gabriela 
Goeuriot, Lorraine 
Iommi, David 
Keller, Jüri 
Knoth, Petr 
Mulhem, Philippe 
Piroi, Florina 
Pride, David 
Schaer, Philipp 
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Organisational Unit: 
E194-04 - Forschungsbereich Data Science 
E058-06 - Fachbereich Zentrum für Forschungsdatenmanagement 
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Published in: 
Experimental IR Meets Multilinguality, Multimodality, and Interaction : 16th International Conference of the CLEF Association, CLEF 2025, Madrid, Spain, September 9–12, 2025, Proceedings 
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ISBN: 
978-3-032-04354-2
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Volume: 
16089
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DOI of the book: 
10.1007/978-3-032-04354-2
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Date (published): 
2026
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Event name: 
16th International Conference of the CLEF Association, CLEF 2025 
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Event date: 
9-Sep-2025 - 12-Sep-2025
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Event place: 
Madrid, Spain
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Number of Pages: 
25
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Publisher: 
Springer, Cham
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Peer reviewed: 
Yes
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Keywords: 
Information Retrieval; Longitudinal Evaluation; Temporal Change; Temporal Generalisability; Temporal Persistence
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Abstract: 
The LongEval lab focuses on the evaluation of information retrieval systems over time. Two datasets are provided that capture evolving search scenarios with changing documents, queries, and relevance assessments. Systems are assessed from a temporal perspective—that is, evaluating retrieval effectiveness as the data they operate on changes. In its third edition, LongEval featured two retrieval tasks: one in the area of ad-hoc web retrieval, and another focusing on scientific article retrieval. We present an overview of this year’s tasks and datasets, as well as the participating systems. A total of 19 teams submitted their approaches, which we evaluated using nDCG and a variety of measures that quantify changes in retrieval effectiveness over time.
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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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