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

نویسندگان

  • Kazi Saidul Hasan
  • Vincent Ng
چکیده

State-of-the-art approaches for unsupervised keyphrase extraction are typically evaluated on a single dataset with a single parameter setting. Consequently, it is unclear 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 understanding of state-of-the-art unsupervised keyphrase extraction algorithms, we conduct a systematic evaluation and analysis of these algorithms on a variety of standard evaluation datasets.

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تاریخ انتشار 2010