Predicting Sequences of User Actions
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Brian D. Davison and
People display regularities in almost everything they do. This paper
proposes characteristics of an idealized algorithm that, when
applied to sequences of user actions, would
allow a user interface to adapt over time 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 at least as good as others that have been considered, while
using fewer computational and memory resources.
Presented at the
Workshop on Predicting the Future: AI Approaches to Time Series Analysis, Madison, WI, July 27, 1998
and published in
Predicting the Future: AI Approaches to Time Series Problems,
Technical Report WS-98-07, pp. 5-12, AAAI Press.
This is a slightly revised and extended version of
Online Action Prediction.
to Brian Davison's publications
Last modified: 31 January 2009
Brian D. Davison