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Decision Tree and MCDA Under Fuzziness to Support E-Customer Satisfaction Survey

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Proceedings of the Tenth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2018) (SoCPaR 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 942))

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Abstract

The proposed work extends existing approaches by analyzing customer click stream data and online reviews to implicitly identify satisfaction level when customer’s rate is not available and find the website criteria score that positively influence e-customer satisfaction. Fuzzy mining customer navigation data is our task to set up inputs of the two proposed supervised evaluation approaches; a multi criteria analysis approach for the website assessment and a new decision tree algorithm to classify customers. A case study from the B2C Chinese website “TMALL” has been used for validating our proposal, and a comparison between the proposed approaches has shown promising results.

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Author information

Authors and Affiliations

  1. Informatics Department, LIM Laboratory, Faculty of Sciences and Techniques of Mohammedia, University Hassan II, Casablanca, Morocco

    Houda Zaim & Mohammed Ramdani

  2. Informatics Department, LAMSAD Laboratory, Superior School of Technology of Berrechid, University Hassan I, Settat, Morocco

    Adil Haddi

Authors
  1. Houda Zaim
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  2. Mohammed Ramdani
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  3. Adil Haddi
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Corresponding author

Correspondence to Houda Zaim .

Editor information

Editors and Affiliations

  1. School of Engineering, Instituto Superior de Engenharia (ISEP/IPP), Porto, Portugal

    Ana Maria Madureira

  2. Machine Intelligence Research Labs (MIR), Auburn, WA, USA

    Ajith Abraham

  3. Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Niketa Gandhi

  4. Politécnico de Leiria, Leiria, Portugal

    Catarina Silva

  5. Politécnico de Leiria, Leiria, Portugal

    Mário Antunes

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Zaim, H., Ramdani, M., Haddi, A. (2020). Decision Tree and MCDA Under Fuzziness to Support E-Customer Satisfaction Survey. In: Madureira, A., Abraham, A., Gandhi, N., Silva, C., Antunes, M. (eds) Proceedings of the Tenth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2018). SoCPaR 2018. Advances in Intelligent Systems and Computing, vol 942. Springer, Cham. https://doi.org/10.1007/978-3-030-17065-3_3

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