A Novel Method for Text Summarization and Clustering of Documents
Raji Ramachandran, Sanju Jayachandran, Vaishnav Das
Abstract
It is now more crucial than ever to offer enhanced methods for accurately and effectively identifying and presenting textual material due to the rapid growth of internet information. Information overload is an issue that has arisen as a result of the vast amount of information that is currently available. A document summary is one potential remedy for the information overload issue. The process of collecting information from a textual document and giving the user the most important content in a condensed form that is responsive to their needs or those of an application is referred as document summarizing. In this study, we provide an autonomous summarising approach that generates a summary for each input document. We also discuss how to achieve discourse coherence in summaries and how to write co-herent, understandable summaries. We also extract the keyword from the many documents that have been provided. Then, using clustering algorithm, we generate clusters based on keyword similarity. Experimentaion results shows that our method can provide efficient clusters of document summeries.