How can deep learning help media makers create content tailored to the reader's preferences? In NewsTAPAS, a project on the personalisation of news, we discovered the need for strengthening automatic capabilities to better summarize articles. Therefore we started working with Natural Language Processing (NLP) and compared recurrent neural networks (RNN), long short-term memory (LTSM), Transformers and their applications within media. In this article we compile some insights and recommendations.

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