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International Conference on Case-Based Reasoning

ICCBR 2012: Case-Based Reasoning Research and Development pp 443–457Cite as

Natural Language Generation through Case-Based Text Modification

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7466))

Abstract

Natural Language Generation (NLG) is one of the longstanding problems in Artificial Intelligence. In this paper, we focus on a subproblem in NLG, namely surface realization through text modification: given a source sentence and a desired change, produce a grammatically correct and semantically coherent sentence that implements the desired change. Text modification has many applications within text generation like interactive narrative systems, where stories tailored to specific users are generated by adapting or instantiating a pre-authored story. We present a case-based approach where cases correspond to pairs of sentences implementing specific modifications. We describe our retrieval, adaptation and revise procedures. The main contribution of this paper is an approach to perform case-adaptation in textual domains.

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Author information

Authors and Affiliations

  1. Computer Science Department, Drexel University, Philadelphia, PA, USA, 19104

    Josep Valls & Santiago Ontañón

Authors
  1. Josep Valls
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  2. Santiago Ontañón
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Editor information

Editors and Affiliations

  1. Universidad Complutense de Madrid, 28040, Madrid, Spain

    Belén Díaz Agudo

  2. Department of Computer Science, University of Auckland, 1142, Auckland, New Zealand

    Ian Watson

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© 2012 Springer-Verlag Berlin Heidelberg

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Valls, J., Ontañón, S. (2012). Natural Language Generation through Case-Based Text Modification. In: Agudo, B.D., Watson, I. (eds) Case-Based Reasoning Research and Development. ICCBR 2012. Lecture Notes in Computer Science(), vol 7466. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32986-9_33

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  • DOI: https://doi.org/10.1007/978-3-642-32986-9_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32985-2

  • Online ISBN: 978-3-642-32986-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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