MaterialBERT for natural language processing of materials science texts

A BERT (Bidirectional Encoder Representations from Transformers) model, which we named “MaterialBERT”, has been generated using scientific papers in wide area of material science as a corpus. A new vocabulary list for tokenizer was generated using material science corpus. Two BERT models with differ...

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Dades bibliogràfiques

Autors principals:	Michiko Yoshitake, Fumitaka Sato, Hiroyuki Kawano, Hiroshi Teraoka
Format:	Artigo
Idioma:	Inglês
Publicat:	Taylor & Francis Group 2022-12-01
Col·lecció:	Science and Technology of Advanced Materials: Methods
Matèries:	word embedding pre-training bert literal information
Accés en línia:	http://dx.doi.org/10.1080/27660400.2022.2124831
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