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Lecture Notes in Computer Science
We consider the problem of predicting how a user will continue a given initial text fragment. Intuitively, our goal is to develop a "tab-complete" function for natural language, based on a model that is learned from text data. We consider two learning mechanisms that generate predictive models from collections of application-specific document collections: we develop an N -gram based completion method and discuss the application of instance-based learning. After developing evaluation metrics fordoi:10.1007/11564096_47 fatcat:lyfgcrdjlvg5doiqzs3qcojage