Text Summarization
Text summarization is a natural language processing (NLP) technique that automatically generates a concise and coherent summary of a longer text document while preserving its key information and meaning. It involves extracting or abstracting the most important points from source material, such as articles, reports, or web pages, to create a shorter version. This process helps users quickly grasp the essence of content without reading the full text.
Developers should learn text summarization when building applications that need to process large volumes of text efficiently, such as news aggregators, research tools, or content management systems. It is particularly useful in scenarios like generating executive summaries from business reports, creating previews for search engine results, or assisting in information retrieval tasks where time and attention are limited.