Most predictive text systems have a user database to facilitate this process. This learning adapts, by way of the device memory, to a user's disambiguating feedback that results in corrective key presses, such as pressing a "next" key to get to the intention. There are many ways to build a device that predicts text, but all predictive text systems have initial linguistic settings that offer predictions that are re-prioritized to adapt to each user. The most widely used, general, predictive text systems are T9, iTap, eZiText, and LetterWise/WordWise. Predictive text makes efficient use of fewer device keys to input writing into a text message, an e-mail, an address book, a calendar, and the like. Predictive text could allow for an entire word to be input by single keypress. Each key press results in a prediction rather than repeatedly sequencing through the same group of "letters" it represents, in the same, invariable order. Predictive text is an input technology used where one key or button represents many letters, such as on the numeric keypads of mobile phones and in accessibility technologies.
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