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Author (up) Palma, D.; Atkinson, J. doi  openurl
  Title Coherence-based Automatic Essay Assessment Type Journal Article
  Year 2018 Publication IEEE Intelligent Systems Abbreviated Journal IEEE Intel. Syst.  
  Volume 33 Issue 5 Pages 26-36  
  Keywords Semantics; Coherence; Feature extraction; Grammar; Intelligent systems; Computational modeling; Measurement; Essay Assessment; Discourse Processing; Semantic Analysis; Machine Learning  
  Abstract In this work, a discourse-based method that merges semantic and syntactic models for automated essay assessment is proposed. The approach combines shallow linguistic features and discourse patterns in order to predict an essay's score by using decision trees regression techniques. Unlike current approaches, our method directly measures an essay coherence by using corpus-based semantics and text centering techniques so as to determine discourse patterns underlying high-quality essays when compared with human assessed essays. Experiments using standard datasets showed that the proposed discourse-based approach outperformed traditional shallow features-based methods.  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1541-1672 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number UAI @ eduardo.moreno @ Serial 947  
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