In this paper, we introduced TextRank -a graphbased ranking model for text processing, and show how it can be successfully used for natural language applications.
we proposed and evaluated two innovative unsupervised approaches for keyword and sentence extraction, and showed that the accuracy achieved by TextRank in these applications is competitive with that of previously proposed state-of-the-art algorithms.