Human-competitive tagging using automatic keyphrase extraction
Medelyan, O., Frank, E. & Witten, I.H. (2009). Human-competitive tagging using automatic keyphrase extraction. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing (pp. 1318-1327), Singapore, 6-7 August 2009 (pp. 1318-1327).
Permanent Research Commons link: https://hdl.handle.net/10289/4886
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.
Association for Computational Linguistics
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