Enhancing Countries’ Fitness with Recommender Systems on the International Trade Network
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 ex...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2018/5806827 |
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| author | Hao Liao Xiao-Min Huang Xing-Tong Wu Ming-Kai Liu Alexandre Vidmer Ming-Yang Zhou Yi-Cheng Zhang |
| author_facet | Hao Liao Xiao-Min Huang Xing-Tong Wu Ming-Kai Liu Alexandre Vidmer Ming-Yang Zhou Yi-Cheng Zhang |
| author_sort | Hao Liao |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-96ddcf8d31d44abd988b05544b0d7ba4 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-96ddcf8d31d44abd988b05544b0d7ba42025-02-03T01:20:37ZengWileyComplexity1076-27871099-05262018-01-01201810.1155/2018/58068275806827Enhancing Countries’ Fitness with Recommender Systems on the International Trade NetworkHao Liao0Xiao-Min Huang1Xing-Tong Wu2Ming-Kai Liu3Alexandre Vidmer4Ming-Yang Zhou5Yi-Cheng Zhang6National Engineering Laboratory for Big Data System Computing Technology, Guangdong Province Key Laboratory of Popular High Performance Computers, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, ChinaNational Engineering Laboratory for Big Data System Computing Technology, Guangdong Province Key Laboratory of Popular High Performance Computers, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, ChinaNational Engineering Laboratory for Big Data System Computing Technology, Guangdong Province Key Laboratory of Popular High Performance Computers, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, ChinaNational Engineering Laboratory for Big Data System Computing Technology, Guangdong Province Key Laboratory of Popular High Performance Computers, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, ChinaNational Engineering Laboratory for Big Data System Computing Technology, Guangdong Province Key Laboratory of Popular High Performance Computers, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, ChinaNational Engineering Laboratory for Big Data System Computing Technology, Guangdong Province Key Laboratory of Popular High Performance Computers, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, ChinaNational Engineering Laboratory for Big Data System Computing Technology, Guangdong Province Key Laboratory of Popular High Performance Computers, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, ChinaPrediction 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.http://dx.doi.org/10.1155/2018/5806827 |
| spellingShingle | Hao Liao Xiao-Min Huang Xing-Tong Wu Ming-Kai Liu Alexandre Vidmer Ming-Yang Zhou Yi-Cheng Zhang Enhancing Countries’ Fitness with Recommender Systems on the International Trade Network Complexity |
| title | Enhancing Countries’ Fitness with Recommender Systems on the International Trade Network |
| title_full | Enhancing Countries’ Fitness with Recommender Systems on the International Trade Network |
| title_fullStr | Enhancing Countries’ Fitness with Recommender Systems on the International Trade Network |
| title_full_unstemmed | Enhancing Countries’ Fitness with Recommender Systems on the International Trade Network |
| title_short | Enhancing Countries’ Fitness with Recommender Systems on the International Trade Network |
| title_sort | enhancing countries fitness with recommender systems on the international trade network |
| url | http://dx.doi.org/10.1155/2018/5806827 |
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