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Abstract:

China has been experiencing rapid growth over the last decade due to economically friendly reforms and a growing skilled and young population. With this increasing growth China's interconnectedness with the global economy has increased significantly. In parallel to this economic evolution, technology has experienced rapid acceleration, which has allowed firms and governments to be able to track and record vast amounts of data. The side effect in this unstructured big data growth is that the datasets are polluted, meaning they can be conflicting, missing and/or unreliable. There is a wide gap in the ability to provide transparency to the exposed importing firms: both timely early warning signals and wide coverage on Small & Medium Enterprises. We have been able to address this problem to our end-users to create transparency in these markets and extract the information value and opinion from a public corpus via deep learning.

China has been experiencing rapid growth over the last decade due to economically friendly reforms and a growing skilled and young population. With this increasing growth China's interconnectedness with the global economy has increased significantly. In parallel to this economic evolution, technology has experienced rapid acceleration, which has allowed firms and governments to be able to track and record vast amounts of data. The side effect in this unstructured big data growth is that the datasets are polluted, meaning they can be conflicting, missing and/or unreliable. There is a wide gap in the ability to provide transparency to the exposed importing firms: both timely early warning signals and wide coverage on Small & Medium Enterprises. We have been able to address this problem to our end-users to create transparency in these markets and extract the information value and opinion from a public corpus via deep learning.

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Topics:
Finance - Deep Learning, AI & Deep Learning Research
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9964
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