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.

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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.

information-overload content-analysis research-efficiency document-digestion
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 8 / 25
Community 15 / 25

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Sep 04, 2020

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