Predicting coauthorship using bibliographic network embedding

Coauthorship prediction applies predictive analytics to bibliographic data to predict authors who are highly likely to be coauthors. In this study, we propose an approach for coauthorship prediction based on bibliographic network embedding through a graph‐based bibliographic data model that can be u...

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Veröffentlicht in:	Journal of the American Society for Information Science and Technology 2023-04, Vol.74 (4), p.388-401
Hauptverfasser:	Zhu, Yongjun, Quan, Lihong, Chen, Pei‐Ying, Kim, Meen Chul, Che, Chao
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Bibliographic literature Bibliographic records Bibliographies Co authorship Data models Embedding Machine learning Predictions Translation Translation methods and strategies Writers
Online-Zugang:	Volltext
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