Madani, O. and Bui, H. and Yeh, E. Efficient online learning and prediction of users’ desktop actions, in IJCAI-2009, pp. 1457-1462, 2009.
We investigate prediction of users’ desktop activities in the Unix domain. The learning techniques we explore do not require explicit user teaching. We show that simple efficient many-class learning can perform well for action prediction, significantly improving over previously published results and baselines. This finding is promising for various human-computer interaction scenarios where a rich set of potentially predictive features is available, where there can be many different actions to predict, and where there can be considerable nonstationarity.