Big data, machine learning and the challenge of the geography of innovation
The geography of innovation is one of the fields of research where the availability of databases is growing fastest, ranging from thousands to millions of georeferenced records such as Espacenet (EPO) or those of WIPO. At the same time, the development of new applications for mapping and data analysis (regression trees, random forest, boost, neural networks, etc.) generates new and exciting possibilities for the analysis of the geographies of innovation.
The session is oriented to the research and exchange of knowledge about georeferenced innovation databases and the use of machine learning and artificial intelligence for the study of the geography of innovation. We encourage the presentation of theoretical and empirical contributions, databases, as well as software and applications that can be used for the analysis of the geography of innovation.