Microsoft Technology Licensing, LLC

Alexander Gautam Primavesi

Piotr Jerzy Holc

Adam John Cudworth

Joseph Charles Woodward

A computer-implemented example generator is described which has a memory storing a text item, examples of use of the text item having been requested. A processor searches at least one n-gram language model to identify n-grams containing the text item. The processor is configured to rank the identified n-grams on the basis of a position of the text item in the identified n-grams; and a user interface presents at least some of the identified n-grams to a user taking into account the ranking.

Data input system/example generator

The description relates to predicting terms based on text inputted by a user. One example includes a computing device comprising a processor configured to send, over a communications network, the text to a remote prediction engine. The processor is configured to send the text to a local prediction engine stored at the computing device, and to monitor for a local predicted term from the local prediction engine and a remote predicted term from the remote prediction engine, in response to the sent text. The computing device includes a user interface configured to present a final predicted term to the user such that the user is able to select the final term. The processor is configured to form the final predicted term using either the remote predicted term or the local predicted term on the basis of a time interval running from the time at which the user input the text.

Remote and local predictions

The description relates to predicting terms based on text inputted by a user. One example can include a computing device comprising a prediction engine stored at the computing device. In this example, the prediction engine has previously been trained to predict terms from text. The computing device also comprises a secondary memory, for example a hard drive, storing a model used by the prediction engine to compute predicted terms from text. The computing device also comprises a primary memory, for example Random Access Memory (RAM), and a processor. The processor is configured to access one or more chunks of the model from the secondary memory based on the text input and to provide the one or more chunks to the primary memory during execution of the prediction engine.

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Alexander Gautam Primavesi