A survey on abstractive text summarization

Abstract

Text Summarization is the task of extracting salient information from the original text document. In this process, the extracted information is generated as a condensed report and presented as a concise summary to the user. It is very difficult for humans to understand and interpret the content of the text. In this paper, an exhaustive survey on abstractive text summarization methods has been presented. The two broad abstractive summarization methods are structured based approach and semantic based approach. This paper collectively summarizes and deciphers the various methodologies, challenges and issues of abstractive summarization. State of art benchmark datasets and their properties are being explored. This survey portrays that most of the abstractive summarization methods produces highly cohesive, coherent, less redundant summary and information rich.