Index Catalog // MDR

Description/Abstract:: The automatic extraction of materials and related properties from the scientific literature is gaining attention in data-driven materials...
Keyword:: tdm, materials science , superconductors, machine learning, and dataset
Resource Type:: Dataset
Data origin:: informatics and data science
Author:: Luca Foppiano
Date Uploaded:: 11/10/2022
Date Modified:: 10/11/2022

Description/Abstract:: The automatic extraction of materials and related properties from the scientific literature is gaining attention in data-driven materials...
Keyword:: tdm, machine learning, materials science, superconductors, and database
Resource Type:: Article
Author:: Foppiano Luca, Pedro Baptista de Castro, Pedro Ortiz Suarez, Kensei Terashima, Yoshihiko Takano, and Masashi Ishii
Date Uploaded:: 11/10/2022
Date Modified:: 08/11/2022

Description/Abstract:: We present Grobid-quantities, an open-source application for extracting and normalising measurements from scientific and patent literatur...
Keyword:: machine learning, physical quantities, and tdm
Resource Type:: Conference Proceeding
Author:: FOPPIANO, Luca, ROMARY, Laurent, ISHII, Masashi, and TANIFUJI, Mikiko
Journal:: DocEng '19: Proceedings of the ACM Symposium on Document Engineering 2019
Date Uploaded:: 15/01/2021
Date Modified:: 01/07/2021

Description/Abstract:: A growing number of papers are published in the area of superconducting materials science. However, novel text and data mining (TDM) pro...
Keyword:: annotation, annotation guidelines, dataset, superconductors, and tdm
Resource Type:: Article
Author:: FOPPIANO, Luca, DIEB, Sae, SUZUKI, Akira, BAPTISTA DE CASTRO, Pedro, IWASAKI, Suguru, UZUKI, Azusa, ESPARZA ECHEVARRIA, Miren Garbine, MENG, Yan, TERASHIMA, Kensei, TAKANO, Yoshihiko, and ISHII, Masashi
Date Uploaded:: 07/01/2021
Date Modified:: 01/07/2021

Description/Abstract:: A growing number of papers are published in the area of superconducting materials science. However, novel text and data mining (TDM) proc...
Keyword:: machine learning, superconductors, and tdm
Resource Type:: Dataset
Data origin:: informatics and data science
Author:: DIEB, Sae, CASTRO, Pedro, ROMARY, Laurent, TAKANO, Yoshihiko, MENG, Yan, UZUKI, Azusa, ESPARZA, Miren, FOPPIANO, Luca, TERASHIMA, Kensei, SUZUKI, Akira, and IWASAKI, Suguru
Date Uploaded:: 07/01/2021
Date Modified:: 14/10/2022

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