抽象的

Automatic Text Summarization Using Regression Model (GA)

Anil Kumar, JyotiYadav, Seema Rani

Text Summarization provide large text data into a shorter version without changing its information content and meaning. It is very difficult for human beings to read whole document to understand and manually summarize the documents. Text Summarization methods are divide into two types: extractive and abstractive summarization. Anabstractive summarization is understanding of document, finding the new concepts and providing summary in few words (sentences different form texts sentences).it is very hard or impossible to design (now a days). In Extractive summarization method select important sentences, paragraphs etc. from the original text document and concatenating them into shorter form. The importance of sentences is decided based on some features of sentences. In this Research paper, Automatic Text Summarization using Extractive techniques with the help of Genetic Algorithm has been presented.

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