I. Introduction
There is a great deal of web content that regularly exhibits the same viewpoint. Thus, it is crucial to summarize unnecessary material. Extractive summary would not be useful when reading summaries of several texts or language that is considerably repetitious since they would be excessively wordy and biased. In addition, as sentences are often longer, non-essential sentence components are frequently added. Since relevant information is distributed across the manuscript, it cannot be included in extractive summaries. The solution to the problem of “dangling” anaphora, which occurs when pronoun-containing sentences are taken out of context and lose their meaning. Although much research has been conducted in the area of extraction based summarization, It is difficult in the terms of abstraction-based summarization for the facile basis that, while computer intelligence can statistically identify the most important sentence in a stanza, it is difficult for them to combine the most principal sentences and produce a concise and coherent summary. Whether it’s the summarization of textual material (such as books, manuscripts etc.) or content consisting of multimedia (such as video transcripts, etc.), the need for high-quality summaries is rising