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

Funders

  • National Key Research and Development Program of China
    China
    Grant ID: 2020YFB0704503
  • Natural Science Foundation of Shanghai
    China
    Grant ID: 20ZR1419000

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