A Comparative Analysis of Sentence Transformer Models for Automated Journal Recommendation Using PubMed Metadata
We present an automated journal recommendation pipeline designed to evaluate the performance of five Sentence Transformer models—all-mpnet-base-v2 (Mpnet), all-MiniLM-L6-v2 (Minilm-l6), all-MiniLM-L12-v2 (Minilm-l12), multi-qa-distilbert-cos-v1 (Multi-qa-distilbert), and all-distilroberta-v1 (robert...
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| Main Authors: | Maria Teresa Colangelo, Marco Meleti, Stefano Guizzardi, Elena Calciolari, Carlo Galli |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
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| Series: | Big Data and Cognitive Computing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-2289/9/3/67 |
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