the analysis utilities and costs to prognose or infer an action that a user desires to be automatically performed in the case of items for example attributes can be words phrases images or other data specific attributes derived therefrom the e g key terms and the classes are categories or areas of interest e g levels of priorities a support vector machine svm is an example of a classifier that can be employed the svm operates by finding a hypersurface in the space of possible inputs that splits the triggering input events from the non triggering events in an optimal way intuitively this makes the classification correct for testing data that is near but not identical to training data other directed and undirected model classification approaches include e g naive bayes bayesian networks decision trees neural networks fuzzy logic models and probabilistic classification models providing different patterns of independence can be employed classification as used herein also is inclusive of statistical regression that is utilized to develop models of priority as will be readily appreciated from the subject specification the subject invention can employ classifiers that are explicitly trained e g via a generic training data as well as implicitly trained e g via observing user behavior receiving extrinsic information for example svm 39 s are configured via a learning or training phase within a classifier constructor and feature selection module thus the classifier s can be employed to automatically learn and perform a number of functions including but not limited to determining what criteria.