Human-competitive tagging using automatic keyphrase extraction

  • Authors:
  • Olena Medelyan;Eibe Frank;Ian H. Witten

  • Affiliations:
  • University of Waikato;University of Waikato;University of Waikato

  • Venue:
  • EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
  • Year:
  • 2009

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Abstract

This paper connects two research areas: automatic tagging on the web and statistical keyphrase extraction. First, we analyze the quality of tags in a collaboratively created folksonomy using traditional evaluation techniques. Next, we demonstrate how documents can be tagged automatically with a state-of-the-art keyphrase extraction algorithm, and further improve performance in this new domain using a new algorithm, "Maui", that utilizes semantic information extracted from Wikipedia. Maui outperforms existing approaches and extracts tags that are competitive with those assigned by the best performing human taggers.