Speaker
Description
In our Directorate F Health, Consumers and Reference Materials at JRC, the Knowledge for Health and Consumer Safety Unit F.7 deals with anticipating knowledge needs, mapping knowledge gaps and suggesting research topics to be carried out in the Directorate and possibly in the JRC. For example, thousands of publications are released every year on different topics where JRC has strong competence and a mandate for scientific advice to European Commission, keep the pace of this continuous growing knowledge is an increasing challenge. The velocity of literature production makes impossible to deliver state of the art answers for EC policy makers without automating the whole process. The only way to face this issue is to apply Machine Learning tools (AI) in the field of Natural Language. The same approach can be used on extracts from raw text, including those from speeches, to reveal sentiments and feelings that can be used to understand trends and (political) shifts that may improve JRC insight in policy developments. We will present examples of benchmarking use of this approach, made by combining tools like Natural Language Understanding IBM Watson and AllenNLP Machine Comprehension models, installed locally at the JRC.
| Desired slot length | 15 minutes |
|---|---|
| Speaker release | Yes |
