Adaptive input interface

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.

A computing device, comprising:

• a processor;
• at least one input detection element;
• at least one display element;
• and
• a memory device including instructions operable to be executed by the processor to perform a set of actions, enabling the computing device to:
• receive user text input via the at least one input detection element;
• compare the user text input against a text repository including a plurality of text items classified according to a probabilistic model to determine at least one predicted input string;
• provide the at east one predicted input string for display on the at least one display element;
• receive, via the at least one input detection element, an indication of a user override of the at least one predicted input string;
• and
• update 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.

One or more non-transitory computer-readable storage media having collectively stored thereon instructions that, when executed by one or more processors of a network system, cause the network system to at least:

• obtain user text input entered by a user into an electronic device;
• determine at least one input prediction by applying a probabilistic model to the user text input and selecting one or more associated text items from a text repository classified according to the probabilistic model;
• transmit information including the at least one input suggestion for presentation to the user on the electronic device;
• receive an indication of a user override of the at least one input suggestion on the electronic device;
• and
• update 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 one or more associated text items that have at least some same text as the user override.