Human-competitive tagging using automatic keyphrase extraction

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.

• Type: Journal
• Year: 2009
• Where: EMNLP
• Authors: Olena Medelyan, Eibe Frank, Ian H. Witten
• Keywords: EMNLP 2009, Keyphrase Extraction, Natural Language Processing, State-of-the-art Keyphrase Extraction, Statistical Keyphrase Extraction