Paper: Conundrums in Unsupervised Keyphrase Extraction: Making Sense of the State-of-the-Art

ACL ID C10-2042
Title Conundrums in Unsupervised Keyphrase Extraction: Making Sense of the State-of-the-Art
Venue International Conference on Computational Linguistics
Session Poster Session
Year 2010
Authors

State-of-the-art approaches for unsuper- vised keyphrase extraction are typically evaluated on a single dataset with a single parameter setting. Consequently, it is un- clear how effective these approaches are on a new dataset from a different domain, and how sensitive they are to changes in parameter settings. To gain a better under- standing of state-of-the-art unsupervised keyphrase extraction algorithms, we con- duct a systematic evaluation and analysis of these algorithms on a variety of stan- dard evaluation datasets.