Document Summarization by Agglomerative nested clustering approach

Digital documents are ubiquitous in this age and every person faces an inundation of data today. In an era where being expeditious in work is becoming a necessity, providing people with the gist of verbose documents is an essential task. Thus in this paper, we document the process of Text Summarization in which a concise summary of a larger text is generated. We propose an Extractive Model of Document Summarization based on Agglomerative clustering which ranks sentences and forms a summary of the highly ranked sentences.