Medelyan, OlenaFrank, EibeWitten, Ian H.2010-12-142010-12-142009Medelyan, 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).https://hdl.handle.net/10289/4886This 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.application/pdfenACL materials are Copyright (C) 1963-2009 ACL; other materials are copyrighted by their respective copyright holders. All materials here are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. Permission is granted to make copies for the purposes of teaching and research.computer sciencekeyphrase extractionMachine learningConference Contribution