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Text summarization is the process of automatically generating a concise and coherent summary of a longer text while preserving its key information.
It plays a vital role in NLP by helping users quickly understand the main points of a document or a set of documents, saving time and effort in information retrieval and decision-making.
There are two main approaches to text summarization: extractive, which selects and combines important sentences from the original text, and abstractive, which generates new sentences to convey the summary.