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An Innovative Approach for the Evaluation of the Web Page Impact Combining User Experience and Neural Network Score

Author

Listed:
  • Alessandro Massaro

    (Dyrecta Lab, Research Institute, 70014 Conversano, Italy)

  • Daniele Giannone

    (Dyrecta Lab, Research Institute, 70014 Conversano, Italy)

  • Vitangelo Birardi

    (Dyrecta Lab, Research Institute, 70014 Conversano, Italy)

  • Angelo Maurizio Galiano

    (Dyrecta Lab, Research Institute, 70014 Conversano, Italy)

Abstract

The proposed paper introduces an innovative methodology useful to assign intelligent scores to web pages. The approach is based on the simultaneous use of User eXperience (UX), Artificial Neural Network (ANN), and Long Short-Term Memory (LSTM) algorithms, providing the web page scoring and taking into account outlier conditions to construct the training dataset. Specifically, the UX tool analyses different parameters addressing the score, such as navigation time, number of clicks, and mouse movements for page, finding possible outliers, the ANN are able to predict outliers, and the LSTM processes the web pages tags together with UX and user scores. The final web page score is assigned by the LSTM model corrected by the UX output and improved by the navigation user score. This final score is useful for the designer by suggesting the tags typologies structuring a new web page layout of a specific topic. By using the proposed methodology, the web designer is addressed to allocate contents in the web page layout. The work has been developed within a framework of an industry project oriented on the formulation of an innovative AI interface for web designers.

Suggested Citation

  • Alessandro Massaro & Daniele Giannone & Vitangelo Birardi & Angelo Maurizio Galiano, 2021. "An Innovative Approach for the Evaluation of the Web Page Impact Combining User Experience and Neural Network Score," Future Internet, MDPI, vol. 13(6), pages 1-21, May.
    • Handle: RePEc:gam:jftint:v:13:y:2021:i:6:p:145-:d:566186
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    References listed on IDEAS

    as
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    5. Xiuming Yu & Meijing Li & Kyung Ah Kim & Jimoon Chung & Keun Ho Ryu, 2016. "Emerging Pattern-Based Clustering of Web Users Utilizing a Simple Page-Linked Graph," Sustainability, MDPI, vol. 8(3), pages 1-18, March.
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