Linguistic Analysis Based Text Shrinking

Abstract

Technology of automatic text summarization plays an important role in information retrieval and text classification, and may provide a solution to the information overload problem. Text summarization is a process of reducing the size of a text while preserving its information content. In this project, I implemented a text shrinking based on summarization of text which takes an input consisting of paragraphs and chooses the most relevant lines based on keyword frequency, title feature, sentence length and sentence position. Then summary is generated based on sorting of these sentences and shrinking percentage. After Summary has been generated certain words are further shrunk in understandable format. Finally a GUI outputs a shrunk stream of text having the most relevant lines.