Augmenting Firm Diversification Behavior Prediction with Graph Embeddings
Resumen
Public procurement plays a crucial role in modern economies, serving not only as a mechanism to acquire public goods, services, and works, but also as a policy tool to foster innovation and development. This chapter uses graph embeddings and machine learning to predict firms’ competitiveness in securing contracts by activity sector, extending activity and technological diversification methods to public procurement markets.
Publicación
In Complex Networks & Their Applications XIV, Studies in Computational Intelligence 1265, Springer
Cristian Candia
Profesor Asociado, Instituto de Data Science, Facultad de Ingeniería, Universidad del Desarrollo, Chile. Director de CRiSS-LAB.
Cristian Candia es científico social computacional y estudia el comportamiento humano y colectivo usando datos a gran escala, ciencia de redes, experimentos e inteligencia artificial.
