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Most existing methods of keyword extraction focus on the manual assignment of keywords by professional curators who may use a fixed taxonomy, or rely on the authors' judgment to provide a representative list. Keyword extraction has combined natural language processing approaches to identify part-of-speech (POS) tags that are combined with supervised learning, machine-learning algorithms, or statistical methods. The existing keyword extraction methods are:
          i) Rapid Automatic Keyword Extraction (RAKE), which is an unsupervised, domain-independent, and language-independent method for extracting keywords from individual documents. [1]
          ii) TextRank.
          iii) .
          iv) .
          v) .
          vi) .
          vii) .
          viii) .

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 [1] Michael W. Berry and Jacob Kogan, Text Mining: Applications and Theory, 2010.