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Identifying important entities in news articles

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[vc_column_text]One of the leading providers of news and intelligence specifically for the global stock markets.[/vc_column_text]

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About this project

[/vc_column_text][vc_row_inner][vc_column_inner width=”1/2″][vc_column_text]Project description

The task was to aggregate lots of financial news articles and they wanted to automatically identify words and phrases that are important for the readers like countries, cities, states, monetary values, units, companies, institutions, etc.

We have used several state of the art Natural Language Processing techniques to perform the Named Entity Recognition task on news articles and present it in a usable way.

[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/2″][vc_column_text]Technologies:

• spaCy, scikit-learn

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