1. A method, comprising: receiving first input data associated with a mobile device, wherein the first input data comprises one or more words; automatically learning user tendencies using the first input data to generate user-specific input history data indicating that at least one input word of the first input data was previously auto-corrected and that the auto-correction was undone; receiving second input data from a touch screen keyboard; analyzing the second input data and at least a portion of the user-specific input history data; and based on the analyzing, providing one or more user-specific auto-corrections or suggestion candidates for the second input data to the touch screen keyboard.
1. A method, comprising: receiving first input data associated with a mobile device, wherein the first input data comprises one or more words; automatically learning user tendencies using the first input data to generate user-specific input history data indicating that at least one input word of the first input data was previously auto-corrected and that the auto-correction was undone; receiving second input data from a touch screen keyboard; analyzing the second input data and at least a portion of the user-specific input history data; and based on the analyzing, providing one or more user-specific auto-corrections or suggestion candidates for the second input data to the touch screen keyboard. 6. The method of claim 1 , wherein: the first input data and the second input data are received at a computing cloud from the mobile device; the mobile device is at a location remote from the cloud; the automatically learning user tendencies occurs in the cloud; the analyzing further comprises combining input history data from two or more distinct users; and the generated auto-corrections or suggestion candidates are provided from the cloud to the mobile device.