Using noun phrase heads to extract document keyphrases

  • Barker K
  • Cornacchia N
  • 1

    Readers

    Mendeley users who have this article in their library.
  • N/A

    Citations

    Citations of this article.

Abstract

© Springer-Verlag Berlin Heidelberg 2000. Automatically extracting keyphrases from documents is a task with many applications in information retrieval and natural language processing. Document retrieval can be biased towards documents containing relevant keyphrases; documents can be classified or categorized based on their keyphrases; automatic text summarization may extract sentences with high keyphrase scores. This paper describes a simple system for choosing noun phrases from a document as keyphrases. A noun phrase is chosen based on its length, its frequency and the frequency of its head noun. Noun phrases are extracted from a text using a base noun phrase skimmer and an off-the-shelf online dictionary. Experiments involving human judges reveal several interesting results: the simple noun phrase-based system performs roughly as well as a state-of-the-art, corpus-trained keyphrase extractor; ratings for individual keyphrases do not necessarily correlate with ratings for sets of keyphrases for a document; agreement among unbiased judges on the keyphrase rating task is poor.

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document

Authors

  • K. Barker

  • N. Cornacchia

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free