repro_eval: A Python Interface to Reproducibility Measures of System-Oriented IR Experiments
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In this work we introduce repro_eval - a tool for reactive reproducibility studies of system-oriented Information Retrieval (IR) experiments. The corresponding Python package provides IR researchers with measures for different levels of reproduction when evaluating their systems’ outputs. By offering an easily extensible interface, we hope to stimulate common practices when conducting a reproducibility study of system-oriented IR experiments.
| Originalsprog | Engelsk |
|---|---|
| Titel | Advances in Information Retrieval - 43rd European Conference on IR Research, ECIR 2021, Proceedings |
| Redaktører | Djoerd Hiemstra, Marie-Francine Moens, Josiane Mothe, Raffaele Perego, Martin Potthast, Fabrizio Sebastiani |
| Antal sider | 6 |
| Forlag | Springer |
| Publikationsdato | 2021 |
| Sider | 481-486 |
| ISBN (Trykt) | 9783030722395 |
| DOI | |
| Status | Udgivet - 2021 |
| Begivenhed | 43rd European Conference on Information Retrieval, ECIR 2021 - Virtual, Online Varighed: 28 mar. 2021 → 1 apr. 2021 |
Konference
| Konference | 43rd European Conference on Information Retrieval, ECIR 2021 |
|---|---|
| By | Virtual, Online |
| Periode | 28/03/2021 → 01/04/2021 |
| Navn | Lecture Notes in Computer Science |
|---|---|
| Vol/bind | 12657 LNCS |
| ISSN | 0302-9743 |
Bibliografisk note
Funding Information:
Acknowledgements. This paper was partially supported by the EU Horizon 2020 research and innovation programme under the Marie Sk lodowska-Curie grant agreement No. 893667, and by the German Research Foundation (No. 407518790).
Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
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