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ISSN 2307-2113 (Electronic)
Revista Cubana de Información en Ciencias de la Salud (ACIMED)

2016, Number 1

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Revista Cubana de Información en Ciencias de la Salud (ACIMED) 2016; 27 (1)

Community detection using co-authorship networks in RDF graphs

Ortiz ME, Hidalgo DY

Language: Spanish
References: 18
Page: 90-99
PDF size: 510.02 Kb.


ABSTRACT

Community detection refers to the problem to identify communities or partitions of nodes that shares common properties in a network. The co-authorship networks are considered complex networks, where the nodes of the network are authors and the edges between nodes provides the co-authorship relationships in one or more publications. In recent years, researches have been carried out with the aim to publish bibliographic metadata following the principles of the linked data. Resulting from this, RDF graphs are obtained, containing the authors and the co-authorship relationships among them. In this paper we propose a method for detecting and visualizing communities in RDF graphs, considering co-authorship relationships as an indicator to measure scientific collaboration. With the implementation of the method proposed, we provide an analysis tool for specialists in information sciences, which improve the process of decision making and implementation of studies in the area.


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