Revving up Sales: Quantifying Automobile Relatedness and Predicting Next Purchase through Network Embeddings

Victor Navarro, Alonso Astroza, Cristian Candia
Last updated on Jun 9, 2026 Industry Collaborations, Applied AI
Image credit: CRiSS-LAB
This research project aims to enhance the decision-making process in the automotive industry. We analyzed the complete circulation permit data from 2016 to 2021 to establish a relational network structure of vehicles and their embedding representation. Then, we developed recommendation systems that were fine-tuned using customer data. Consequently, the project intends to provide valuable insights for decision-making that can cater to the needs of current and future customers.

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Network Science Decision Making Business Analytics Machine Learning Network Embeddings Data Science
Victor Navarro
Victor Navarro
Data Scientist
Cristian Candia
Cristian Candia
Associate Professor, Data Science Institute, School of Engineering, Universidad del Desarrollo, Chile. Head of CRiSS-LAB.

Cristian Candia studies how societies transform information into collective relevance through attention, memory, preferences, and coordination. His work combines computational social science, network science, AI, and large-scale behavioral data to understand how groups, institutions, and societies decide what matters.