Analysing research collaboration through co-authorship networks in a big data environment: an efficient parallel approach-Reference-Cited by-同舟云学术

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Analysing research collaboration through co-authorship networks in a big data environment: an efficient parallel approach

Published:2020 Issue:3 Volume:21 Page:364
ISSN:1742-7185
Container-title:International Journal of Computational Science and Engineering
language:en
Short-container-title:IJCSE

Author:

Valêncio Carlos Roberto,Jos& N.A.,eacute N.A.,Freitas Carlos De,Rog& N.A.,eacute N.A.,Grat& ria Cristiane,atilde N.A.,Souza o De,Neves Leandro Alves,Zafalon Geraldo Francisco Donegá,Colombini Angelo Cesar,Tenório William

Publisher

Inderscience Publishers

Subject

Computational Theory and Mathematics,Computational Mathematics,Hardware and Architecture,Modelling and Simulation,Software

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Federated Learning with Internet of Things for Data Privacy and Security;2023 International Conference on Networking and Communications (ICNWC);2023-04-05

2. A survey on federated learning applications in healthcare, finance, and data privacy/data security;ETLTC-ICETM2023 INTERNATIONAL CONFERENCE PROCEEDINGS: ICT Integration in Technical Education & Entertainment Technologies and Management;2023

3. Applications of federated learning in smart cities: recent advances, taxonomy, and open challenges;Connection Science;2021-06-04

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