Using Noun Phrase Heads to Extract Document Keyphrases

@inproceedings{Barker2000UsingNP,
  title={Using Noun Phrase Heads to Extract Document Keyphrases},
  author={Ken Barker and Nadia Cornacchia},
  booktitle={Canadian Conference on AI},
  year={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… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 12 references

Flexible Summarization

  • Delannoy, Jean-François, +4 authors Stan Szpakowicz
  • AAAI Spring Symposium Workshop on Intelligent…
  • 1998
1 Excerpt

The Design of a Configurable Text Summarization System

  • Barker, Ken, Yllias Chali, Terry Copeck, Stan Matwin, Stan Szpakowicz
  • TR-98-04, School of Information Technology and…
  • 1998
1 Excerpt

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