Abstractive Summarization using Graph Based Methods

In the era of big data, resources are bountiful. Text summarization is a necessary and research area that minifies text such that repeated data are removed and important information is extracted and represented in the concise way which can help us to understand the information instantly. There are two approaches of text summarization mainly classified into Extractive and Abstractive. However, Extractive summary can be generated by extracting key features from the original document and fuse them into a shorter version but it has limitation that it never generates human level summaries for large documents. Abstractive Summarization(AS) understands the whole document and creates a concise and instructive version of a text document by extracting important information from the original document and generating new sentences using that information. Structured and Semantic are the two basic approaches of Abstractive Summarization. Graph based method from both the approaches are the one of the method used for summarization. Our work will mainly focus on the analysis details of how Graph based technique can be used to generate a condensed version of original document in abstractive summarization.