Human-competitive tagging using automatic keyphrase extraction
|Human-competitive tagging using automatic keyphrase extraction|
|Author(s)||Medelyan O., Frank E., Witten I.H.|
|Published in||EMNLP 2009 - Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: A Meeting of SIGDAT, a Special Interest Group of ACL, Held in Conjunction with ACL-IJCNLP 2009|
|Keyword(s)||Unknown (Extra: Automatic tagging, Folksonomies, Keyphrase extraction, Research areas, Semantic information, Wikipedia, Algorithms, Computational linguistics, Semantics, User interfaces, Natural language processing systems)|
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Human-competitive tagging using automatic keyphrase extraction is a 2009 conference paper written in English by Medelyan O., Frank E., Witten I.H. and published in EMNLP 2009 - Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: A Meeting of SIGDAT, a Special Interest Group of ACL, Held in Conjunction with ACL-IJCNLP 2009.
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.
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