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Have you ever summarized a lengthy document into a short paragraph? How long did you take? Manually generating a summary can be time consuming and tedious. Automatic text summarisation promises to overcome such difficulties and allow you to generate the key ideas in a piece of writing easily.
Text summarisation is the technique for generating a concise and precise summary of voluminous texts while focusing on the sections that convey useful information, and without losing the overall meaning.
Automatic text summarisation aims to transform lengthy documents into shortened versions, something which could be difficult and costly to undertake if done manually. Machine learning algorithms can be trained to comprehend documents and identify the sections that convey important facts and information before producing the required summarized texts.
With the present explosion of data circulating the digital space, which is mostly non-structured textual data, there is a need to develop automatic text summarisation tools that allow people to get insights from them easily. Currently, we enjoy quick access to enormous amounts of information. However, most of this information is redundant, insignificant, and may not convey the intended meaning. For example, if you are looking for specific information from an online news article, you may have to dig through its content and spend a lot of time weeding out the unnecessary stuff before getting the information you want. Therefore, using automatic text summarisers capable of extracting useful information that leaves out inessential and insignificant data is becoming vital. Implementing summarisation can enhance the readability of documents, reduce the time spent in researching for information, and allow for more information to be fitted in a particular area.
Life is too short to read all the articles, blog posts, research papers you wanted to. So, don’t waste your time reading lengthy documents & really, really long articles.
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