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 Natural Language Processing is one of the key areas where Machine Learning has been very effective. In fact, whereas NLP traditionally required a lot of human intervention, today, this is no longer true. Specifically, Deep Learning technology can be used for learning tasks related to language, such as translation, classification, entity recognition or in this case, summarization.
 
-Summarization is the task of condensing a piece of text to a shorter version, reducing the size of the initial text while at the same time preserving key informational elements and the meaning of content. Since manual text summarization is a time expensive and generally laborious task, the automatization of the task is gaining increasing popularity and therefore constitutes a strong motivation for academic research.
 
 There are important applications for text summarization in various NLP related tasks such as text classification, question answering, legal texts summarization, news summarization, and headline generation. Moreover, the generation of summaries can be integrated into these systems as an intermediate stage which helps to reduce the length of the document.