4. A computer-implemented method for intelligently predicting user input entered on a computing device, comprising: receiving, on the computing device, user text input; accessing a text repository including a plurality of text items classified according to a probabilistic model; inferring, using a processor of the computing device, one or more input predictions by applying the probabilistic model to the user text input; presenting, using a visual output element of the computing device, a suggested text based on the one or more input predictions; receiving, on the computing device, an indication of a user override of the suggested text; and updating at least one probability of the probabilistic model, the at least one probability corresponding to the user override, wherein the at least one probability is based at least in part upon an average probability of one or more other probabilities of the probabilistic model when the user override is a new probability of the probabilistic model, the one or more other probabilities corresponding to the text items that have at least some same text as the user override.
11. The computer-implemented method of claim 4 , wherein the probabilistic model comprises a Bayesian network, an n-gram model, or a hidden Markov model.