The academic world utterly relies on the concept of scientific collaboration. As in every collaborative network, however, the production of research articles follows hidden co-authoring principles as well as temporal dynamics which generate latent and complex collaboration patterns. In this paper, we present an online advanced tool for real-time rankings of computer scientists under these perspectives. © Springer International Publishing AG 2016.

Ranking researchers through collaboration pattern analysis

DI CARO, Luigi;SCHIFANELLA, CLAUDIO
2016-01-01

Abstract

The academic world utterly relies on the concept of scientific collaboration. As in every collaborative network, however, the production of research articles follows hidden co-authoring principles as well as temporal dynamics which generate latent and complex collaboration patterns. In this paper, we present an online advanced tool for real-time rankings of computer scientists under these perspectives. © Springer International Publishing AG 2016.
2016
15th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2016;
Riva del Garda
19 September 2016 through 23 September 2016
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
9853 LNCS
50
54
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84988637674&doi=10.1007%2f978-3-319-46131-1_11&partnerID=40&md5=33c16a8f659910d5b2d18f7ab97d3f1f
Artificial intelligence; Complex networks, Authors ranking; Bibliometrics; Collaboration patterns; Collaborative network; Computer scientists; Real time; Scientific collaboration; Temporal dynamics, Learning systems; Authors ranking; Bibliometrics; Collaboration patterns
Cataldi, Mario; Di Caro, Luigi; Schifanella, Claudio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1639627
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