Mining scientific databases for territorial intelligence
Christine Largeron, Sylvie Chalaye · International Journal of Reasoning-based Intelligent Systems · 2009
Today, economic growth depends more and more on innovation and network alliance. In the context of innovation clusters (poles of competency), decision makers need information about the innovation capacity of their territory and the organisation of research activities for a local geographical area (region, department, etc.). The paper presents a local technology intelligence system for measuring the level of knowledge creation and analysing scientific cooperations. This decision support system is based on knowledge discovery in bibliographic databases providing geographical locations. Through the use of data mining algorithms, it helps in analysing the complexity of territorial networks. We illustrate this approach through a case study of an urban area (Sud Loire, City of Saint-Etienne, France).