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    • UNIR REVISTAS
    • Revista IJIMAI
    • 2012
    • vol. 1, nº 6, september 2012
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    • UNIR REVISTAS
    • Revista IJIMAI
    • 2012
    • vol. 1, nº 6, september 2012
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    Improving Web Learning through model Optimization using Bootstrap for a Tour-Guide Robot

    Autor: 
    León, Rafael
    ;
    Rainer, J. Javier
    ;
    Rojo, José Manuel
    ;
    Galán, Ramón
    Fecha: 
    09/2012
    Palabra clave: 
    web mining; supervised learning; bootstrap; patterns mining; web classifiers; knowledge management; IJIMAI
    Revista / editorial: 
    International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)
    Tipo de Ítem: 
    article
    URI: 
    https://reunir.unir.net/handle/123456789/9603
    DOI: 
    http://dx.doi.org/10.9781/ijimai.2012.162
    Dirección web: 
    https://www.ijimai.org/journal/node/273
    Open Access
    Resumen:
    We perform a review of Web Mining techniques and we describe a Bootstrap Statistics methodology applied to pattern model classifier optimization and verification for Supervised Learning for Tour-Guide Robot knowledge repository management. It is virtually impossible to test thoroughly Web Page Classifiers and many other Internet Applications with pure empirical data, due to the need for human intervention to generate training sets and test sets. We propose using the computer-based Bootstrap paradigm to design a test environment where they are checked with better reliability.
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    Nombre: IJIMAI20121_6_2.pdf
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