Abstract
The intensive use of the Web, email and instant messaging for inter- and intra-business communications has resulted in rapid increase of electronic business communication, including negotiations. Simulated electronic negotiations have become an important tool in the study of “real world” electronic negotiations. We explore negotiation strategies by applying Statistical Natural Language Processing and Machine Learning methods to the text data of simulated electronic negotiations. We derive conclusions about strategies in successful and unsuccessful negotiations. We support our claims by extracting information about strategies and representing data through this information. We classify data and analyze classification results with respect to learning abilities of the classifiers and the data representation.
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Sokolova, M., Szpakowicz, S. (2005). Analysis and Classification of Strategies in Electronic Negotiations. In: Kégl, B., Lapalme, G. (eds) Advances in Artificial Intelligence. Canadian AI 2005. Lecture Notes in Computer Science(), vol 3501. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11424918_16
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DOI: https://doi.org/10.1007/11424918_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25864-3
Online ISBN: 978-3-540-31952-8
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