An Ensemble of Automatic Keyword Extractors: TextRank, RAKE and TAKE

Authors

  • Tayfun Pay Graduate Center of New York, Computer Science Department New York, United States
  • Stephen Lucci The City College of New York, Computer Science Department New York, United States
  • James L. Cox Brooklyn College of New York, Computer and Information Science Department Brooklyn, United States

DOI:

https://doi.org/10.13053/cys-23-3-3234

Keywords:

Data mining, text mining, text analysis, ensemble methods

Abstract

We construct an ensemble method for automatic keyword extraction from single documents. We utilize three different unsupervised automatic keyword extractors in building our ensemble method. These three approaches provide candidate keywords for the ensemble method without using their respective threshold functions. The ensemble method combines these candidate keywords and recomputes their scores after applying pruning heuristics. It then extracts keywords by employing dynamic thres hold functions. Weanalyze the performance of our ensemble method by using all parts of the Inspect data set. Our ensemble method achieved a better overall performance when compared to the automatic keyword extractors that were used in its development as well as to some recent automatic keyword extraction methods.

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Published

2019-09-25

Issue

Vol. 23 No. 3 (2019): Thematic issue: Computational Linguistics (Guest Editor A. Gelbukh)

Section

Articles of the Thematic Issue

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