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Discovering Web Users’ Web Access Pattern Based on Psychology

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Intelligent Communication Technologies and Virtual Mobile Networks (ICICV 2019)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 33))

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Abstract

The web access behaviour of the web users is influenced by customers’ state of mind. The influence of the customers’ psychology in web access behaviour is analysed in this paper. Positive emotion along with positive mood induces better attitude in the web users’ behaviour whereas negative emotion along with negative mood induces a negative attitude among web users. The state of human mind changes along with the temporal property based on the emotion and mood. The statistical study on the historical data is used to discover the influence of mental state which affects the web users’ behaviour. Various machine learning algorithms along with statistics and psychology are studied to discover the knowledge about the web users’ access behaviour.

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Author information

Authors and Affiliations

  1. Computer Science and Engineering, Francis Xavier Engineering College, Tirunelveli, India

    E. Manohar

  2. Electrical and Electronics Engineering, Panimalar Engineering College, Chennai, India

    E. Anandha Banu

Authors
  1. E. Manohar
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  2. E. Anandha Banu
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Corresponding author

Correspondence to E. Manohar .

Editor information

Editors and Affiliations

  1. Department of CSE, Francis Xavier Engineering College, Tirunelveli, Tamil Nadu, India

    S. Balaji

  2. Departamento de Engenharia Informática, Faculdade de Ciências e Tecnologia, University of Coimbra, Coimbra, Portugal

    Álvaro Rocha

  3. Department of Electrical Engineering, National Changhua University of Education, Changhua County, Taiwan

    Yi-Nan Chung

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Manohar, E., Anandha Banu, E. (2020). Discovering Web Users’ Web Access Pattern Based on Psychology. In: Balaji, S., Rocha, Á., Chung, YN. (eds) Intelligent Communication Technologies and Virtual Mobile Networks. ICICV 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 33. Springer, Cham. https://doi.org/10.1007/978-3-030-28364-3_28

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  • DOI: https://doi.org/10.1007/978-3-030-28364-3_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-28363-6

  • Online ISBN: 978-3-030-28364-3

  • eBook Packages: EngineeringEngineering (R0)

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