Automatic Text Summarization using Text Rank Algorithm

Automatic text summarization has been emerged as a valuable tool for quickly locating the significant information in vast text with minimal effort. The practice of constructing a summarized form of a text document that retains significant information and also withstand the overall meaning of the source text is known as text summarization. This study mainly concentrates on the extractive text summarization technique wherein the text summarization is carried out on single document as well as on multi document text. Further, the application is extended by implementing document summarization and URL summarization. Here, the sentence extraction method from the input text forms the basis of proposed text summarization technique. During sentence extraction, the weights are assigned to sentences which act as rank of these sentences, using page rank algorithm. In this study, extraction technique has been implemented to extract sentences having higher rank from the given input text. The study mainly focuses on obtaining high rank sentences from the given document in order to generate a high-quality summary of the input text.