Enhancing Countries’ Fitness with Recommender Systems on the International Trade Network
Joint Authors
Zhang, Yi-Cheng
Liao, Hao
Vidmer, Alexandre
Zhou, Ming-Yang
Huang, Xiao-Min
Wu, Xing-Tong
Liu, Ming-Kai
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-10-18
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Liao, Hao& Huang, Xiao-Min& Wu, Xing-Tong& Liu, Ming-Kai& Vidmer, Alexandre& Zhou, Ming-Yang…[et al.]. 2018. Enhancing Countries’ Fitness with Recommender Systems on the International Trade Network. Complexity،Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1134793
Modern Language Association (MLA)
Liao, Hao…[et al.]. Enhancing Countries’ Fitness with Recommender Systems on the International Trade Network. Complexity No. 2018 (2018), pp.1-12.
https://search.emarefa.net/detail/BIM-1134793
American Medical Association (AMA)
Liao, Hao& Huang, Xiao-Min& Wu, Xing-Tong& Liu, Ming-Kai& Vidmer, Alexandre& Zhou, Ming-Yang…[et al.]. Enhancing Countries’ Fitness with Recommender Systems on the International Trade Network. Complexity. 2018. Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1134793
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1134793