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Using Noun Phrase Heads to Extract Document Keyphrases (2000)
| Citations: | 75 - 0 self |
BibTeX
@MISC{Barker00usingnoun,
author = {Ken Barker and Nadia Cornacchia},
title = {Using Noun Phrase Heads to Extract Document Keyphrases},
year = {2000}
}
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Abstract
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. 1
Keyphrases
noun phrase head document keyphrases noun phrase keyphrase rating task off-the-shelf online dictionary individual keyphrases high keyphrase score relevant keyphrases unbiased judge many application document retrieval information retrieval human judge corpus-trained keyphrase extractor natural language processing simple system simple noun phrase-based system automatic text summarization head noun base noun phrase skimmer several interesting result
