Summarize sentence6/12/2023 The positive side of the explosion of written content available online is that we now have more training data we can use to create advanced summarization models. This is where automatic text summarization comes in. Unless, of course, we can summarize it intelligently. but the amount of text generated far outpaces our ability to process it. This text may contain vital information for businesses, brands, financial asset traders, etc. Everything from tweets, to news articles, to blog posts includes text. In recent years, this area has become a particular point of interest due to the explosion of written content available online. In this article, you will mostly focus on the most common type of automatic summarization: automatic text summarization. Humans, like machines, have a finite amount of data you can process per given unit of time and while you can't make your brain work faster (yet), you can certainly condense the information, essentially achieving a higher throughput of data processed per unit of time. It's important to note that, here, by 'resources' we mean both computer resources involved in data processing, but also human cognitive resources required to parse and understand text. What Questions Can Machine Learning Help You Answer?.The end goal, whether we summarize text, images or videos, is to reduce the amount of resources required to transmit and process data. Wikipedia defines automatic summarization as " the process of shortening a set of data computationally, to create a subset (a summary) that represents the most important or relevant information within the original content". In fact, you can "summarize" images and videos as well as text. Therefore, systems that can extract the core ideas from text and preserve the overall meaning stand to revolutionize entire industries, from health care to law, to finance, by allowing you to share information faster and more efficiently.Īutomatic summarization as a field is not limited to text. A large amount of the information we create and exchange is in written form. This is not to say that text summarization is of little importance, quite the contrary. What is the Difference Between Data Analytics, Predictive Analytics, and Data Science?.How to Use Machine Learning to Automate Tasks.It is an area of computer automation that has seen steady development and improvement, although it does not get as much press as other machine learning achievements. How to Use the PEGASUS Model for Abstractive Text SummarizationĪutomatic text summarization comprises a set of techniques that use algorithms to condense a large body of text, while at the same time preserving the important information included in the text.What Are Transformers in Abstractive Summarization?.How to Use the Text Rank Algorithm for Extractive Text Summarization.What Are the Main Types of Text Summarization.Why You Should Care About Summarization.
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