Automatic Classification of Industrial Accident Causes using NLP: A Case Study in eMARS
This study proposes a lightweight Natural Language Processing (NLP) pipeline to automatically classify the primary cause of major accidents using the European eMARS database and shows that Word2Vec+SVM provides the strongest and most stable baseline on the full labelled set, while SBERT performance improves markedly un...
Valerio Cozzani, B. Fabiano, G. Reniers et al.
· 0 citations