Abstract
The paper shows how to construct language patterns that signal influence strategies and tactical moves corresponding to such strategies. We apply corpus analysis methods to the extraction of certain multi-word patterns from the text data of electronic negotiations. The patterns thus acquired become features in the task of classifying those texts. A series of machine learning experiments predicts the negotiation outcome from the texts associated with first halves of negotiations. We compare the results with the classification of complete negotiations.
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Sokolova, M., Szpakowicz, S. (2006). Language Patterns in the Learning of Strategies from Negotiation Texts. In: Lamontagne, L., Marchand, M. (eds) Advances in Artificial Intelligence. Canadian AI 2006. Lecture Notes in Computer Science(), vol 4013. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11766247_25
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DOI: https://doi.org/10.1007/11766247_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34628-9
Online ISBN: 978-3-540-34630-2
eBook Packages: Computer ScienceComputer Science (R0)