A social network analysis based approach to extracting knowledge patterns about innovation geography from patent databases
by Massimiliano Ferrara; Diego Fosso; Davide Lanatà; Roberto Mavilia; Domenico Ursino
International Journal of Data Mining, Modelling and Management (IJDMMM), Vol. 10, No. 1, 2018

Abstract: Patents have been one of the main topics investigated in several fields of scientific literature. Currently, data about patents is rapidly increasing, and the adoption of data mining and big-data-centred approaches to investigating them appears compulsory. Among these last approaches, social network analysis (SNA) is extremely promising. In this paper, we propose an SNA-based approach to extracting knowledge patterns about patent inventors and their collaborations. Our approach is extremely general and can be exploited to investigate patents of any country. It allows the analysis of some issues that have not been considered in the past, such as the presence of 'power inventors' in a country, the existence of a backbone and of possible cliques among them, the influence and the benefits of power inventors on their co-inventors and, more in general, in the R&D activities of their country. All these issues represent innovation geography knowledge patterns that can be extracted, thanks to our approach.

Online publication date: Fri, 02-Feb-2018

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