Abstract
The analysis of scientific collaboration networks has contributed significantly to improve the understanding of the collaboration process between researchers. Additionally, it has helped to understand how scientific productions by researchers and research groups evolve. However, the identification of collaborations in large scientific databases is not a trivial task, given the high computational cost of the prevalent methods. This paper proposes a method for identifying collaborations in large scientific databases, namely, ISColl – Identification of Scientific Collaboration. Unlike methods that use techniques such as exhaustive comparisons of publication pairs, the proposed method produces satisfactory results with a low computational cost, thus providing an interesting alternative for the modelling and characterization of large scientific collaboration networks. To demonstrate the potential of the proposed technique, tests were conducted using scientific publications data registered in the Lattes Platform of CNPq, with the obtained results yielding excellent accuracy during the identification of scientific collaborations.
Highlights
The production and publication of scientific papers have increased considerably in recent years
In addition to scholarly or scientific production, there has been a steady growth in the study of networks in relation to various disciplines ranging from computer science and communication to sociology and epidemiology
The metrics adopted to verify the results were based on the principle of precision and recall. These metrics are commonly used in Information Retrieval (IR) systems
Summary
The production and publication of scientific papers have increased considerably in recent years. The rapid proliferation of research publications on the Internet can be considered as the primary factor accelerating the distribution of this class of publications. Services such as digital libraries, social networks, websites and bibliographic repositories that act as a personal storehouse for an individual’s scholarly or scientific productions are some examples of how the Internet has. The abovementioned topics have been studied by several researchers; it was only recently that the analysis of networks has become an important area of research. This is partly due to the advancement of computers. Computers have aided in the empirical study of real networks, and have enabled researchers from different fields to conduct technical analyses of large networks
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
