Improving web learning through model optimization using bootstrap for a tour-guide robot

León, Rafael, Rainer Granados, José Javier, Rojo, José Manuel and Galán López, Ramón ORCID: https://orcid.org/0000-0001-6395-7991 (2012). Improving web learning through model optimization using bootstrap for a tour-guide robot. "International Journal of Artificial Intelligence and Interactive Multimedia", v. 1 (n. 6); pp. 13-19. ISSN 1989-1660. https://doi.org/10.9781/ijimai.2012.162.

Descripción

Título: Improving web learning through model optimization using bootstrap for a tour-guide robot
Autor/es:
Tipo de Documento: Artículo
Título de Revista/Publicación: International Journal of Artificial Intelligence and Interactive Multimedia
Fecha: Septiembre 2012
ISSN: 1989-1660
Volumen: 1
Número: 6
Materias:
ODS:
Palabras Clave Informales: Bootstrap, Knowledge Management, Patterns Mining, Supervised Learning, Web Classifiers, Web Mining
Escuela: E.T.S.I. Industriales (UPM)
Departamento: Automática, Ingeniería Electrónica e Informática Industrial [hasta 2014]
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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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.

Más información

ID de Registro: 16361
Identificador DC: https://oa.upm.es/16361/
Identificador OAI: oai:oa.upm.es:16361
Identificador DOI: 10.9781/ijimai.2012.162
URL Oficial: http://www.ijimai.org/journal/node/273
Depositado por: Memoria Investigacion
Depositado el: 19 Ene 2014 08:41
Ultima Modificación: 21 Abr 2016 16:40