pradeepdev-1995/Text-summarization-natural-language-processing
Text summarization refers to the technique of shortening long pieces of text. The intention is to create a coherent and fluent summary having only the main points outlined in the document. Automatic text summarization is a common problem in machine learning and natural language processing (NLP).Text summarization is the problem of creating a short, accurate, and fluent summary of a longer text document. Automatic text summarization methods are greatly needed to address the ever-growing amount of text data available online to both better help discover relevant information and to consume relevant information faster.
This tool helps you quickly get the main points from long documents by automatically shortening them. You provide a lengthy text, and it outputs a concise, coherent summary, allowing you to consume information faster. It's ideal for anyone who needs to process large volumes of written information efficiently, such as researchers, analysts, or content managers.
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Use this if you need to quickly grasp the core ideas from extensive articles, reports, or web pages without reading every word.
Not ideal if you require a summary that captures every nuance or highly specific detail of the original text.
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Sep 04, 2020
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