Abstract: A data input system is described which has a user interface which receives one or more context text items in a sequence of text items input by a user. A processor of the data input system uses a plurality of language models to predict, from each language model, a next item in the sequence of text items. The processor uses a dynamic model which is bespoke to the user as a result of learning text items which the user has previously used, to predict a next item in the sequence of text items. The processor weights the predicted next item from the dynamic model using at least per term weights, each per term weight representing a likelihood of an associated term of the dynamic model given one of the language models.

Abstract: A data input system is described which has a user interface which receives one or more context text items in a sequence of text items input by a user. A processor of the data input system uses a plurality of language models to predict, from each language model, a next item in the sequence of text items. The processor uses a dynamic model which is bespoke to the user as a result of learning text items which the user has previously used, to predict a next item in the sequence of text items. The processor weights the predicted next item from the dynamic model using at least per term weights, each per term weight representing a likelihood of an associated term of the dynamic model given one of the language models.