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Learning User Intentions in Natural Language Call Routing Systems

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Recent Developments and New Direction in Soft-Computing Foundations and Applications

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 342))

Abstract

The context analysis of customer requests in a natural language call routing problem is investigated in this paper. Understanding of customer intention is one of the most important problems in natural language call routing. The adaptive neuro-fuzzy inference system is examined for solving this problem. This system can be applied to any language call routing domain; that is, there is no lexical or syntactic analysis used in the classification.

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Authors and Affiliations

  1. Institute of Control Systems of Azerbaijan National Academy of Sciences, Baku, Azerbaijan

    Kamil Aida-zade & Samir Rustamov

Authors
  1. Kamil Aida-zade
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  2. Samir Rustamov
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Corresponding author

Correspondence to Kamil Aida-zade .

Editor information

Editors and Affiliations

  1. University of California, Berkeley, USA

    Lotfi A. Zadeh

  2. Tech. of the Republic of Azerbaijan, Ministry of Communications Info., Baku, Azerbaijan

    Ali M. Abbasov

  3. Machine Intelligence Institute, New Rochelle, New York, USA

    Ronald R. Yager

  4. Azerbaijan Technical University, Baku, Azerbaijan

    Shahnaz N. Shahbazova

  5. University of Alberta, Edmonton, Alberta, Canada

    Marek Z. Reformat

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Aida-zade, K., Rustamov, S. (2016). Learning User Intentions in Natural Language Call Routing Systems. In: Zadeh, L., Abbasov, A., Yager, R., Shahbazova, S., Reformat, M. (eds) Recent Developments and New Direction in Soft-Computing Foundations and Applications. Studies in Fuzziness and Soft Computing, vol 342. Springer, Cham. https://doi.org/10.1007/978-3-319-32229-2_4

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  • DOI: https://doi.org/10.1007/978-3-319-32229-2_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32227-8

  • Online ISBN: 978-3-319-32229-2

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