Authors:
Annamaria Demarinis Loiotile
1
;
2
;
Francesco De Nicolò
1
;
2
;
Alfonso Monaco
1
;
Sabina Tangaro
3
;
Shiva Loccisano
4
;
Giuseppe Conti
5
;
Adriana Agrimi
6
;
Nicola Amoroso
7
and
Roberto Bellotti
1
Affiliations:
1
Dipartimento Interateneo di Fisica, Università degli Studi di Bari Aldo Moro, Bari, Italy
;
2
Dipartimento di Ingegneria Elettrica e dell’Informazione, Politecnico di Bari, Bari, Italy
;
3
Dipartimento di Scienze del Suolo, della Pianta e degli Alimenti, Università degli Studi di Bari Aldo Moro, Bari, Italy
;
4
Behold srl, Bologna, Italy
;
5
Netval – Network per la Valorizzazione della Ricerca Universitaria, Lecco, Italy
;
6
Direzione Ricerca, Terza Missione e Internazionalizzazione, Università degli Studi di Bari Aldo Moro, Bari, Italy
;
7
Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari Aldo Moro, Bari, Italy
Keyword(s):
Natural Language Processing, Italian Patents, Intellectual Property Analytics, Clustering, Technology Transfer, Knowledge Database, Healthcare 4.0.
Abstract:
A great mine of innovation is represented by the excellence of the scientific know-how of the Italian universities and research centers. But very often university patents remain unvalued and unexploited, in the so-called “Valley of death”. In the framework of Intellectual Property Analytics and Patent Informatics, this paper analyses the Italian patent database “Knowledge Share” and its proposed classifications (10 technological areas). By means of Natural Language Processing (NLP) techniques, we examined 1694 patents from 89 Italian Research Institutions and a cluster analysis revealed the existence of 8 homogeneous clusters instead of the 10 proposed by the platform. Thus, our findings suggest the presence of possible inhomogeneities within the traditional classifications, probably due to the emergence of novel technologies or cross-domain areas, e.g., Healthcare 4.0; moreover, these clusters could lead to better performance in terms of offer/demand matching for the platform users.