RepositoryPlease use this identifier to cite or link to this item:
http://hdl.handle.net/11366/2722| Title: | AI for Duplicate Record Detection in Current Research Information System | Authors: | Dornbusch, Joachim | Keywords: | artificial intelligence;research information management;deduplication;large language models;current research information systems;case studies | Issue Date: | 24-Apr-2025 | Publisher: | euroCRIS | Conference: | Second online meeting of the AI4CRIS Working Group | Abstract: | The presentation provides a case study on the application of artificial intelligence to research information management for the purpose of identifying duplicate records for publications. This is an ongoing area of activity of the CRISalid consortium formed by twelve institutions in France, https://crisalid.org/. The slides describe the process to detect duplicates for publications without any shared identifiers. Several data sources are harvested for the purpose of collecting a full bibliography, the ultimate objective being to help research institutions overcome the choice between commercial turnkey systems and the fragmented ecosystem of open platforms. |
Description: | 12 slides.-- For more info, see the CRIS2024 Conference presentation on the SoVisu+ model at http://hdl.handle.net/11366/2578. |
URI: | http://hdl.handle.net/11366/2722 |
| Appears in Collections: | euroCRIS TG Outputs |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| JDornbusch_CRISalid_AI-for-duplicate-record-detection-in-CRIS_AI4CRIS_20250424.pdf | Presentation (PDF) | 1.68 MB | Adobe PDF | View/Open |
Page view(s)
31
checked on May 21, 2025
Download(s)
11
checked on May 21, 2025
Google ScholarTM
Check
Items in DSpace are offered under a CC-BY 4.0 licence unless otherwise indicated