Molecular Connections built the Journal Recommendation Service for IFIS, a society publisher in food and health sciences, to help authors choose a journal for a manuscript and to steer submissions away from predatory journals. Users search and browse the FSTA database of trusted journals by keyword or journal title, filter results by criteria such as open access options and Impact Factor, and can adjust their title, abstract and research areas to find a better match. The service covers over 1,000 food-focused and interdisciplinary journals and uses deep learning models, including BERT.
Benefits & outcomes
- Molecular Connections reports a 30% increase in traffic.
- Molecular Connections reports that new journals can be added with minimal retraining.
Publisher / company: IFISMolecular Connections
Date of case study: Not stated
Status: Not stated
Built by: Vendor working with a publisher
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