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World is observing an explosion of unstructured data today, a significant part of it, is in text form. One of the most effective text analytics techniques is extraction of keywords. Keywords provide information to obtain the summary of a document and they help in correlating documents. The main challenge is in identifying keywords from the document that are of the interest. In this paper, the authors aim to find meaningful keywords and create an automatic summary. They also compare and investigate a range of graph based ranking algorithms, and evaluate their application to automatic unsupervised Keyword extraction in the context of a text summarization task.