Experiments in UNIX Command Prediction
Paper (15 pages)
Brian D. Davison and
A good user interface is central to the success of most products.
Our research is concerned
with improving an interface by making it adaptive --- changing over time as
it learns more about the user.
In this paper we consider the task of modifying a UNIX shell to
learn to predict the next command executed as one sample adaptive
user interface. To this end, we
have collected command histories (some extensive) from 77
people, and have calculated the predictive accuracy for each of five methods
over this dataset. The algorithm with the highest performance produces an
average online predictive accuracy of up to 38%.
Machine Learning Technical Report #41, Department of Computer Science, Rutgers University.
to Brian Davison's publications
Last modified: August 24, 1997
Brian D. Davison