Journal article classification using abstracts: a comparison of classical and transformer-based machine learning methods Universiteit Antwerpen
In this article we analyze the performance of existing models to classify journal articles into disciplines from a predefined classification scheme (i.e., supervised learning), based on their abstract. The first part analyzes scenarios with ample labeled data, comparing the performance of the Support Vector Machine algorithm (SVM) combined with TF-IDF and with SPECTER embeddings (Cohan et al. SPECTER: Document-level representation learning using ...