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      • Department of Computer Engineering
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      Keyphrase extraction through query performance prediction

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      Author
      Ercan, G.
      Cicekli, I.
      Date
      2012
      Source Title
      Journal of Information Science
      Print ISSN
      0165-5515
      Publisher
      Sage Publications Ltd.
      Volume
      38
      Issue
      5
      Pages
      476 - 488
      Language
      English
      Type
      Article
      Item Usage Stats
      139
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      111
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      Abstract
      Previous research shows that keyphrases are useful tools in document retrieval and navigation. While these point to a relation between keyphrases and document retrieval performance, no other work uses this relationship to identify keyphrases of a given document. This work aims to establish a link between the problems of query performance prediction (QPP) and keyphrase extraction. To this end, features used in QPP are evaluated in keyphrase extraction using a naïve Bayes classifier. Our experiments indicate that these features improve the effectiveness of keyphrase extraction in documents of different length. More importantly, commonly used features of frequency and first position in text perform poorly on shorter documents, whereas QPP features are more robust and achieve better results. © 2012 The Author(s).
      Keywords
      Keyphrase extraction
      Query performance prediction
      Bayes classifier
      Document retrieval
      Keyphrase extraction
      Query performance prediction
      Information science
      Information systems
      Information retrieval
      Permalink
      http://hdl.handle.net/11693/21321
      Published Version (Please cite this version)
      http://dx.doi.org/10.1177/0165551512448984
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      • Department of Computer Engineering 1368
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