This paper1 presents a Web adaptation and personalization architecture that uses cognitive aspects as its core filtering element. The innovation of the proposed architecture focus...
Sampling is a popular way of scaling up machine learning algorithms to large datasets. The question often is how many samples are needed. Adaptive stopping algorithms monitor the ...
We consider the problem of one-step ahead prediction for time series generated by an underlying stationary stochastic process obeying the condition of absolute regularity, describi...
Reusable adaptation specifications for adaptive behaviour has come to the forefront of adaptive research recently, with EU projects such as GRAPPLE1, and PhD research efforts on de...
Alexandra I. Cristea, David Smits, Jon Bevan, Maur...
This overview article reviews the structure of a fully statistical spoken dialogue system (SDS), using as illustration, various systems and components built at Cambridge over the ...