Dataset of ‘A Literature Mining Method of Fusing Text and Table Extraction in Materials Science’

Published: 14 November 2022| Version 1 | DOI: 10.17632/jxk2pmh8bt.1
Contributor:
Jiawang Zhang

Description

We propose a named entity recognition model for material text, called SciBERT-Fasttext-BiLSTM-CRF (SFBC). We used this model to identify named entities from texts in the stainless steel scientific literature and shared data on the frequency of occurrence of selected entities in this database between 2012 and 2021. By analysing the data in this dataset, researchers are able to understand the top research trends in stainless steel materials over the last decade.

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Institutions

Shanghai University

Categories

Materials Science, Artificial Intelligence, Data Mining

Funding

National Key Research and Development Program of China

2020YFB0704503

Natural Science Foundation of Shanghai

20ZR1419000

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