Probabilistic Online Action Prediction
Short Paper (7 pages):
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(98kb)
Brian D. Davison and
Haym 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