The evaluation of abstractive text summarization using deep learning.

From numerous sources, a vast volume of text data has been developing daily. This enormous volume of data contains crucial knowledge and information that must be skillfully condensed to be usable. In this era of digitalization, vast information is available to us, which are being uploaded online from all over the world in the form of the web pages, and social media etc. To expand quick knowledge from this massive content, the summary of text can help understand the concept fast. Whenever we talk about the text summarization in research article or paper, we must be aware that this colossal amount of data can be generic or scientific and with this we will have an astronomical number of publications. There would be great support to the researchers if the approach of automatically summarization were applied on the scientific articles to increase the speed of understanding. Due of its applicability in numerous fields, automatic summarization of natural language is a prominent academic and industrial focus in computer science. While doing text summarization the essence or the context of the text remains same this could be the primary requirement. It is due to the high usage of Internet as a medium text summarization is developed as an outstanding tool for interpreting text information. Extraction of important information from the source text material is known as text summarization. In this procedure, the extracted data is produced as a concise report and sent to the user as a succinct summary. Broadly text summarization is classified into two methods extractive and abstractive techniques for summarization. Defining a rank from the text file based on the word and features of the sentence, collate them to develop a summary where feature of sentences will be notified based on the statistical and linguistic trait, which we name as extractive summarization method. In other case first we have to understand the details and main points of the documents, after which we need to define these concept in terms of natural language is defined as Abstractive Summarization method. This paper will give you the comparative study of various Abstractive Summarization methods. [ABSTRACT FROM AUTHOR]