Probabilistic Online Action Prediction (original) (raw)

Short Paper (7 pages):Publisher Version, Local Postscript(98kb)
Brian D. Davison andHaym Hirsh

Abstract
People display regularities in almost everything they do. This paper proposes characteristics of an idealized algorithm that would allow a user interface to adapt to an individual's pattern of use. We describe a simple predictive method with these characteristics and show its predictive accuracy on a large dataset of UNIX commands to be better than others that have been considered, while using fewer computational and memory resources.

Presented at the AAAI Spring Symposium on Intelligent Environments, March 23-25, 1998, Stanford University, California and published in Intelligent Environments: Papers from the AAAI 1998 Spring Symposium, Technical Report SS-98-02, pp. 148-154: AAAI Press.

A slightly revised and extended version of this paper is available as Predicting Sequences of User Actions.

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Last modified: 31 January 2009
Brian D. Davison