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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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
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