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
ACL 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.