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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

SciKGraph: A knowledge graph approach to structure a scientific field

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Author(s):
Tosi, Mauro Dalle Lucca [1] ; dos Reis, Julio Cesar [2]
Total Authors: 2
Affiliation:
[1] Univ Luxembourg, Fac Sci Technol & Commun, Belval - Luxembourg
[2] Univ Estadual Campinas, Inst Comp, Campinas, SP - Brazil
Total Affiliations: 2
Document type: Journal article
Source: Journal of Informetrics; v. 15, n. 1 FEB 2021.
Web of Science Citations: 0
Abstract

Understanding the structure of a scientific domain and extracting specific information from it is laborious. The high amount of manual effort required to this end indicates that the way knowledge has been structured and visualized until the present day should be improved in software tools. Nowadays, scientific domains are organized based on citation networks or bag-of-words techniques, disregarding the intrinsic semantics of concepts presented in literature documents. We propose a novel approach to structure scientific fields, which uses semantic analysis from natural language texts to construct knowledge graphs. Then, our approach clusters knowledge graphs in their main topics and automatically extracts information such as the most relevant concepts in topics and overlapping concepts between topics. We evaluate the proposed model in two datasets from distinct areas. The results achieve up to 84% of accuracy in the task of document classification without using annotated data to segment topics from a set of input documents. Our solution identifies coherent keyphrases and key concepts considering the dataset used. The SciKGraph framework contributes by structuring knowledge that might aid researchers in the study of their areas, reducing the effort and amount of time devoted to groundwork. ? 2020 Elsevier Ltd. All rights reserved. (AU)

FAPESP's process: 13/08293-7 - CCES - Center for Computational Engineering and Sciences
Grantee:Munir Salomao Skaf
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC
FAPESP's process: 17/02325-5 - EvOLoD: linked data evolution on the Semantic Web
Grantee:Julio Cesar dos Reis
Support Opportunities: Research Grants - Young Investigators Grants