Abstract
The extraction of multi-document summarization (MDS) has become the dominant technique to offer a compact form of documents that manages the opposite characteristic of the real documents. This technique finds the subset of similarity from the input documents (words/phrases/sentences) in the original text to form the summary in contrast. This paper has illustrated upon the similarity between the MDS problem with the vertex cover problem (VCP) and some important factors for the effective implementation of vertex cover algorithm (VCA) identified through a systematic review of the literature using SMART (Specific, Measurable, Assignable, Realistic, Time related) target. Further, they are categorized into five fields namely text summarization, MDS, Automatic text summarization, Sentence extraction, and Graph-based summarization and the lesson learned from these studies are discussed. The results of the research demonstrate the effectiveness of the proposed method in graph-based automatic multi-document summarization.
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