Identification of relevant experts using academic social network mining
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Publication Details
Author list: Nakornpanom D.N., Prom-On S.
Publisher: Hindawi
Publication year: 2017
Start page: 711
End page: 714
Number of pages: 4
ISBN: 9781509060870
ISSN: 0146-9428
eISSN: 1745-4557
Languages: English-Great Britain (EN-GB)
Abstract
The necessary operation in every sector of organization is finding a talented or experienced individual to participate in a team that will handle specific tasks. Having the right people in the team would increase the team performance and allow the team to be more effective in delivery the result. Research and development play important roles in the development of science and technology. Peer-reviewed publication is one of the main methods used for evaluating research. Normally, editor of academic journal will find researchers for reviewing research based on mainly the research network. However, there are various and interdisciplinary types of thesis nowadays. They made more difficult results for finding reviewers. This paper aims to develop the system for automatically suggest relevant experts given the task of reviewing the scientific paper. This inevitably would assure the quality of the research process and provide an effective way to manage the publication cycle. The system will automatically find related reviewer for reviewing papers based on the co-author networks, reference network and the reputation model. ฉ 2017 IEEE.
Keywords
Editor of academic journal, Peer-reviewed publication, Peer-reviewed system, Research network, Styling
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