Text Summarization Using NLP

Abstract

This Project represents the work related to Text Summarization. In this paper, we present a framework for summarizing the huge information. The proposed framework depends on highlight extraction from the internet, utilizing both morphological elements and semantic data. Presently, where huge information is available on the internet, it is most important to provide improved ways to extract the information quickly and most efficiently. It is very difficult for human beings to manually extract the summary of a large document of text. There are plenty of text materials available on the internet. So, there is a problem of searching for related documents from the number of documents available and absorbing related information from it. In essence to figure out the previous issues, automatic text summarization is very much necessary. Text Summarization is the process of identifying the most important and meaningful information in an input document or set of related input documents and compressing all the inputs into a shorter version while maintaining its overall objectives.