Improving Web Learning through model Optimization using Bootstrap for a Tour-Guide Robot

Authors

Rafael León
Javier Rainer
José Manuel Rojo
Ramón Galán

DOI

10.9781/ijimai.2012.162

Abstract

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.

Source Publication

International Journal of Interactive Multimedia and Artificial Intelligence

Recommended Citation

León, Rafael; Rainer, Javier; Rojo, José Manuel; and Galán, Ramón (2012) "Improving Web Learning through model Optimization using Bootstrap for a Tour-Guide Robot," International Journal of Interactive Multimedia and Artificial Intelligence: Vol. 1: Iss. 6, Article 4.
DOI: 10.9781/ijimai.2012.162
Available at: https://ijimai.researchcommons.org/ijimai/vol1/iss6/4