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

Author
Keywords
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.
Year of Publication
2012
Journal
International Journal of Interactive Multimedia and Artificial Intelligence
Volume
1
Issue
Special Issue on Intelligent Systems and Applications
Number
6
Number of Pages
13-19
Date Published
09/2012
ISSN Number
1989-1660
Citation Key
URL
http://www.ijimai.org/journal/sites/default/files/IJIMAI20121_6_2.pdf
DOI
10.9781/ijimai.2012.162
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