Intelligent Export Diversification : An Export Recommendation System with Machine Learning /
This paper presents a set of collaborative filtering algorithms that produce product recommendations to diversify and optimize a country's export structure in support of sustainable long-term growth. The recommendation system is able to accurately predict the historical trends in export content...
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| Format: | Journal |
| Language: | English |
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Washington, D.C. :
International Monetary Fund,
2020.
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| Series: | IMF Working Papers; Working Paper ;
No. 2020/175 |
| Online Access: | Full text available on IMF |
| Summary: | This paper presents a set of collaborative filtering algorithms that produce product recommendations to diversify and optimize a country's export structure in support of sustainable long-term growth. The recommendation system is able to accurately predict the historical trends in export content and structure for high-growth countries, such as China, India, Poland, and Chile, over 20-year spans. As a contemporary case study, the system is applied to Paraguay, to create recommendations for the country's export diversification strategy. |
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| Item Description: | <strong>Off-Campus Access:</strong> No User ID or Password Required <strong>On-Campus Access:</strong> No User ID or Password Required |
| Physical Description: | 1 online resource (46 pages) |
| Format: | Mode of access: Internet |
| ISSN: | 1018-5941 |
| Access: | Electronic access restricted to authorized BRAC University faculty, staff and students |