Liao, Hao Huang, Xiao-Min Wu, Xing-Tong Liu, Ming-Kai Vidmer, Alexandre Zhou, Ming-Yang Zhang, Yi-Cheng 2018 Prediction is one of the major challenges in complex systems. The prediction methods have shown to be effective predictors of the evolution of networks. These methods can help policy makers to solve practical problems successfully and make better strategy for the future. In this work, we focus on exporting countries’ data of the International Trade Network. A recommendation system is then used to identify the products that correspond to the production capacity of each individual country but are somehow overlooked by the country. Then, we simulate the evolution of the country’s fitness if it would have followed the recommendations. The result of this work is the combination of these two methods to provide insights to countries on how to enhance the diversification of their exported products in a scientific way and improve national competitiveness significantly, especially for developing countries. application/pdf https://folia.unifr.ch/global/documents/307508 https://folia.unifr.ch/documents/307508/files/zha_ecf.pdf eng info:eu-repo/semantics/altIdentifier/doi/10.1155/2018/5806827 info:eu-repo/semantics/openAccess License undefined Complexity. - 2018, vol. 2018, p. 5806827 info:eu-repo/classification/udc/53 Enhancing countries’ fitness with recommender systems on the international trade network http://purl.org/coar/resource_type/c_6501