A document discusses the importance of summarization techniques for processing large amounts of text data. It notes that automatic summarization systems aim to generate concise summaries while retaining the most important information. The document examines an unsupervised method for multi-document summarization that clusters sentences from multiple texts on a topic together and selects the most representative sentences to include in a summary. The method aims to generate summaries in 3 sentences or less to provide users with the key details and essence of the original documents.

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