Any language we speak can be learned. People have been doing it for a very long time and they do it very successfully. But computers, unfortunately, still have problems with understanding natural languages, but people are still trying to teach it to computing machines almost since their inception. Around the same time NLP (Natural Language Processing), which means "natural language processing", appeared in computer science. It includes quite a few serious problems, and summarization is one of them.
Let's imagine that someone read the large text we need and then underlined the main information with a pencil. Obviously, it would be more convenient and faster to read such a variant. This method of summarization is called extractive. It was the first one that appeared, so it is not without its disadvantages. The program may be shown the selected text fragments, and then it will make an abridged variant out of them. But the program doesn't know what is important and what is not. Fortunately, with the development of neural networks, an abstract summarization has appeared. The new method works like this: the algorithm takes the source text as the basis, and gives a brief extract, which may contain no words from the taken material. If all of the above is "run" through such an algorithm, the output will be something like this: Summarization or autoreferencing is the automatic creation of a brief version of the source text by the algorithm, preserving the original meaning.
Everyone has to deal with large volumes of text in one way or another, so summarization can be useful for everyone. School and university students can quickly extract basic information from the articles, notes and other study materials they need for their studies. In a condensed form, it is much easier to learn and absorb it all. This means that preparing for exams, homework and other types of academic activity will be much easier for pupils and students. For example, anyone can master War and Peace, and the content of the book will be quick and straightforward to digest. Well, or at least get some idea of it, which in itself is useful.
Journalists, SEO-specialists, advertisers and copywriters often work with topics that are new to them. To do this, they first need to study the subject about which they are writing. This takes up quite a lot of time and effort. If the topic is complicated, you can "bury yourself" in it for days or even weeks. Instead of that, they can resort to the self-learning algorithm to summarize the articles and other sources they need. A brief extract of basic information on the subject interesting for the commercial author will be much more useful than thick reference books or lengthy arguments of bloggers and experts.
The algorithm of the service ReText.AI , which knows how to work with the volume of text, adapting to certain requirements, can help in this. It is known that each social network has restrictions on the number of characters. For example, Twitter has a maximum post length of only 280 characters, Instagram - 2,200. The channel description at Telegram, like its name, holds only 255 characters, and the length of the post is equal to 4096 letters or characters. Everyone who works with one or several social networks at once knows this. Therefore, the author needs to adjust what is written to the limitations dictated by this or that site. You can adapt a large text initially created for Telegram to Twitter, Instagram or Facebook manually. It will take you about half an hour or an hour. An experienced author will probably manage it much faster, in about 20 minutes. But a text summarization service can change the text almost instantly.
Using the opportunity of ReText.AI to change the text online, even a novice author can quickly and qualitatively "brush up" all the materials for publication at the necessary platform. All you need to do is to insert the source text into the editor at ReText.AI and choose the social network for which the project is adapted. You can also simply specify the number of characters you need in the output. After that the service will analyze the written text by itself, and then it will provide a fully finished material.
So far ReText.AI summarization is at the beta-testing stage, but the developers intend to complete it very soon. Then the service will be able to extract the essence from various texts and will be useful not only for students, copywriters and advertisers, but also for others. For example, lawyers, doctors or officials.