author keywords: NER; Technical language processing; TLP; Word2Vec; Topic modeling

TL;DR: This work presents a supervised machine learning approach to categorize unstructured text from 500K+ manufacturing science related scientific abstracts and labelling them under various manufacturing topic categories, using the developed NER model as a Technical Language Processing (TLP) workflow on manufacturing science documents. (via Semantic Scholar)