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sis 18(16): e14

Research Article

Knowledge Extraction Using Web Usage Mining

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  • @ARTICLE{10.4108/eai.13-4-2018.154551,
        author={Muhammad  Waqas and Maria  Iram and Sara  Shahzad and Sidra  Arshad and Tahir Nawaz },
        title={Knowledge Extraction Using Web Usage Mining},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={5},
        number={16},
        publisher={EAI},
        journal_a={SIS},
        year={2018},
        month={4},
        keywords={Data Mining, Web Usage Mining, Web Mining, Knowledge Extraction, KD, WWW},
        doi={10.4108/eai.13-4-2018.154551}
    }
    
  • Muhammad Waqas
    Maria Iram
    Sara Shahzad
    Sidra Arshad
    Tahir Nawaz
    Year: 2018
    Knowledge Extraction Using Web Usage Mining
    SIS
    EAI
    DOI: 10.4108/eai.13-4-2018.154551
Muhammad Waqas1,*, Maria Iram1,*, Sara Shahzad2,*, Sidra Arshad, Tahir Nawaz ,*
  • 1: University of Lahore, Sargodha, Pakistan
  • 2: UOP
*Contact email: hwr44ever@gmail.com, merum2@gmail.com , sarashahzad2@gmail.com, tahir.nawaz@cs.uol.edu.pk

Abstract

Web log files are the greatest source of knowledge now days, which keeps all the information about users interaction to web. This interaction provides us the usage patterns of the user by using web usage mining. These files contain all the information about visitors of the web which is used as input for analysis. These files are converted to required formats after completing the preprocessing so Web Usage Mining (WUM) techniques can apply on these logs. Web usage mining gives us the details of user patterns. In this study we are going discover different behaviors patterns from the web proxy server log file of an educational organization with web usage mining technique. Results are based on the interest of users towards educational websites.

Keywords
Data Mining, Web Usage Mining, Web Mining, Knowledge Extraction, KD, WWW
Received
2017-12-22
Accepted
2018-01-10
Published
2018-04-20
Publisher
EAI
http://dx.doi.org/10.4108/eai.13-4-2018.154551

Copyright © 2018 Muhammad Waqas et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.

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