01265nas a2200253   4500000000100000000000100001008004100002260001200043653001500055653002400070653001400094653002000108653002500128100001700153700001800170700002200188700001800210245009300228856007400321300001000395490000600405520058600411022001400997       2012                            d  c09/201210aWeb Mining10aSupervised Learning10aBootstrap10aPatterns Mining10aKnowledge Management1 aRafael León1 aJavier Rainer1 aJosé Manuel Rojo1 aRamón Galán00aImproving Web Learning through model Optimization using Bootstrap for a Tour-Guide Robot  uhttp://www.ijimai.org/journal/sites/default/files/IJIMAI20121_6_2.pdf  a13-190 v13 aWe 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.  a1989-1660