Creating research topic map for NIMS SAMURAI database using natural language processing approach

Creating research topic map for NIMS SAMURAI database using natural language processing approach

In this study, we present an approach to create a visual research topic map for materials science researchers from a large collection of archived research papers using natural language processing (NLP). We apply this approach on SAMURAI, a directory service for the researchers of the National Instit...

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Bibliographic Details
Main Authors: Sae Dieb, Kou Amano, Kosuke Tanabe, Daitetsu Sato, Masashi Ishii, Mikiko Tanifuji
Format: Article
Language:English
Published: Taylor & Francis Group 2021-01-01
Series:Science and Technology of Advanced Materials: Methods
Subjects:
text and data mining
materials science
word cloud
topic visualization
topic map
Online Access:http://dx.doi.org/10.1080/27660400.2021.1899426

Internet

http://dx.doi.org/10.1080/27660400.2021.1899426

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