AIDME: A Scalable, Interpretable Framework for AI-Aided Scoping Reviews.
Michael Soprano|Sandip Modha|Kevin Roitero|Eddy Maddalena|Marco Viviani|Gabriella Pasi|Stefano Mizzaro
| Anthology ID: | DBLP:conf/ictir/SopranoMRM0PM25 |
|---|---|
| Volume: | Proceedings of the 2025 International ACM SIGIR Conference on Innovative Concepts and Theories in Information Retrieval, ICTIR 2025, Padua, Italy, 18 July 2025 |
| Year: | 2025 |
| Venue: | International Conference on the Theory of Information Retrieval (ICTIR) |
| Publisher: | ACM |
| Pages: | 194-207 |
| URL: | https://doi.org/10.1145/3731120.3744586 |
| DOI: | https://doi.org/10.1145/3731120.3744586 |
| DBLP: | conf/ictir/SopranoMRM0PM25 |
| BibTeX: |
@inproceedings{soprano-2025-aidme,
author = {Michael Soprano and
Sandip Modha and
Kevin Roitero and
Eddy Maddalena and
Marco Viviani and
Gabriella Pasi and
Stefano Mizzaro},
editor = {Hamed Zamani and
Laura Dietz and
Benjamin Piwowarski and
Sebastian Bruch},
title = {{AIDME: A Scalable, Interpretable Framework for AI-Aided Scoping Reviews}},
booktitle = {{Proceedings of the 2025 International ACM SIGIR Conference on Innovative Concepts and Theories in Information Retrieval, ICTIR 2025, Padua, Italy, 18 July 2025}},
pages = {194--207},
publisher = {ACM},
year = {2025},
url = {https://doi.org/10.1145/3731120.3744586},
doi = {https://doi.org/10.1145/3731120.3744586}
}