We propose an active learning algorithm that learns a continuous valuation model from discrete preferences. The algorithm automatically decides what items are best presented to an...
Many applications refer to moving objects or phenomena and require spatio-temporal modelling and specific analysis. Unlike conventional data where attributes are simple values (nu...
In this paper we show that financial information can be used to sense many aspects of human activity. This simple technique gives people information about their daily lives, is ea...
Julia Schwarz, Jennifer Mankoff, H. Scott Matthews
Inductive Logic Programming (ILP) is a combination of inductive learning and first-order logic aiming to learn first-order hypotheses from training examples. ILP has a serious b...
One very important application in the data mining domain is frequent pattern mining. Various authors have worked on improving the efficiency of this computation, mostly focusing o...