Unstructured Text Summarization Approach in the Age of Big Data: A Review

Abstract

Text summarization is the task of reducing a text document with help of a software in order to generate a summary that retains the most important parts of the original document. It is not simple for individuals to manually summarize expansive reports of content information, Because of the a lot of content information being produced and associations expanded quickly with the accessibility of Big Data platforms, there is no enough time to peruse and perceive all document and make judgments based on text stuffing. Therefore, there is a great demand for summarizing text documents to deliver a demonstrative substitute for the novel documents. There are two techniques to summarize a text document 1) extractive summarization and 2) abstractive summarization. It is not easy task for people to manually summarize large documents of text data. An extractive summarization technique Chooses vital sentence, content etc. from the original text document and joined them into shorter structure to form outline. An abstractive summarization technique comprehend the original text data and re-telling it in fewer words to generate outline. In this survey paper, we exhibit an overview and Comparative Analysis of Unstructured Text Summarization Approach in the Age of Big Data.