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Case Retrieval Reuse Net (CR2N): An Architecture for Reuse of Textual Solutions

  • Ibrahim Adeyanju
  • Nirmalie Wiratunga
  • Robert Lothian
  • Somayajulu Sripada
  • Luc Lamontagne
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5650)

Abstract

This paper proposes textual reuse as the identification of reusable textual constructs in a retrieved solution text. This is done by annotating a solution text so that reusable sections are identifiable from those that need revision. We present a novel and generic architecture, Case Retrieval Reuse Net (CR2N), that can be used to generate these annotations to denote text content as reusable or not. Obtaining evidence for and against reuse is crucial for annotation accuracy, therefore a comparative evaluation of different evidence gathering techniques is presented. Evaluation on two domains of weather forecast revision and health & safety incident reporting shows significantly better accuracy over a retrieve-only system and a comparable reuse technique. This also provides useful insight into the text revision stage.

Keywords

Case Grouping Case Base Reasoning Retrieval Accuracy Textual Unit Natural Language Generation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Ibrahim Adeyanju
    • 1
  • Nirmalie Wiratunga
    • 1
  • Robert Lothian
    • 1
  • Somayajulu Sripada
    • 2
  • Luc Lamontagne
    • 3
  1. 1.School of ComputingRobert Gordon UniversityAberdeenScotland, UK
  2. 2.Department of Computing ScienceUniversity of AberdeenAberdeenScotland, UK
  3. 3.Department of Computer Science and Software EngineeringUniversité Laval, Québec(Québec)Canada

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