ew 21(33): e12

Research Article

Intelligent Systems of Machine Learning Approaches for Developing E-Services Portals

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  • @ARTICLE{10.4108/eai.2-12-2020.167292,
        author={Waleed M. Ead and Mohamed M. Abbassy},
        title={Intelligent Systems of Machine Learning Approaches for Developing E-Services Portals},
        journal={EAI Endorsed Transactions on Energy Web},
        volume={8},
        number={33},
        publisher={EAI},
        journal_a={EW},
        year={2020},
        month={12},
        keywords={Intelligent Servers, Web Logs, Data Mining, E-Services, E-Commerce, energy-saving applications, Machine Learning Approaches},
        doi={10.4108/eai.2-12-2020.167292}
    }
    
  • Waleed M. Ead
    Mohamed M. Abbassy
    Year: 2020
    Intelligent Systems of Machine Learning Approaches for Developing E-Services Portals
    EW
    EAI
    DOI: 10.4108/eai.2-12-2020.167292
Waleed M. Ead1,*, Mohamed M. Abbassy1
  • 1: Faculty of Computers and Artificial Intelligence, Beni-Suef University, Egypt
*Contact email: Waleedead@bsu.edu.eg

Abstract

This paper provides a framework for intelligent servers that provide e-services on portals and applications for e-commerce purposes, such as an intelligent server that can dynamically plan and structure to respond to future users' needs and provide the appropriate e-services at the right time. To figure out how web users learn the log files collected from web users' connections and the internet, we use data mining techniques. In our experimental study, we use real data sets. Different data mining techniques are also used for Developing Intelligent E-Services Portals in future work, and it is a very difficult task in big data to identify regular trends. As the duration of the trends has to be discovered to expand the analytical space thatgrows exponentially.