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by Vishal Chahal, Balaji Kadambi | Updated June 28, 2018 - Published September 7, 2017
Artificial intelligenceData sciencePython
Watson Natural Language Understanding requires multiple documents for training in order to obtain good results. In new subject domains, there is limited time to create multiple training documents. In such a scenario, the approach suggested in this developer journey augments the results from Natural Language Understanding with a simple input configuration JSON file, which can be prepared by a domain expert. This approach gives accurate results without the need for training documents.
In this pattern, we show you how to use Watson Natural Language Understanding (NLU) service and IBM Watson Studio to augment the text classification results when there is no historical data available. A configuration JSON document prepared by a domain expert is taken as input by IBM Watson Studio. The configuration JSON document can be modified to obtain better results and insights into the text content.
When you have completed this pattern, you will understand how to:
Ready to put this code pattern to use? Complete details on how to get started running and using this application are in the README.
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