16. The method of claim 3 , wherein said analyzing said plurality of returned mark-up language documents further comprises determining at least one difference in metadata phrases between a lower ranked returned mark-up language document and a higher ranked returned mark-up language document.
16. The method of claim 3 , wherein said analyzing said plurality of returned mark-up language documents further comprises determining at least one difference in metadata phrases between a lower ranked returned mark-up language document and a higher ranked returned mark-up language document. 19. The method of claim 16 , wherein said supervised training procedure comprises one or more of the following approaches and methods: analytical learning, artificial neural network, Backpropagation, Bayesian analysis, Decision Trees, Case Based Reasoning, Inductive Logic Programming, Gaussian process regression, Kernel estimators, Learning Automata, Minimum message length, Naive bayes classifier, Nearest Neighbor Algorithm, Probably approximately correct learning, Ripple down rules, Symbolic machine learning algorithms, Subsymbolic machine learning algorithms, Support vector machines, Random Forests, Ensembles of Classifiers, Ordinal Classification, Data Pre-processing, Handling imbalanced datasets, Statistical relational learning.