Results for tag: "Text Summarization"

Text summarization is a Natural Language Processing (NLP) task that involves condensing a text document into a shorter version while preserving its key points. It is used to reduce the time and effort required to read and understand a text document. Text summarization can be done in two ways: extractive and abstractive. Extractive summarization involves selecting important sentences from the original text and combining them to form a summary. Abstractive summarization involves generating a summary from scratch using the key points of the original text. Text summarization is used in a variety of applications, such as summarizing news articles, legal documents, and medical records. It is also used to generate summaries of customer reviews and feedback, which can help businesses better understand customer sentiment. Some companies in the text summarization market include Automated Insights, Narrative Science, Lexalytics, and Yseop. Show Less Read more