Credit scoring is a method of modelling potential risk of credit applications. Traditionally, logistic regression, linear regression and discriminant analysis are the most popular...
Context can be seen as a paradigm aiming to improve user interaction with software. For Web applications in particular, the issues of content explosion and technological constrain...
We present an adaptation technique for statistical machine translation, which applies the well-known Bayesian learning paradigm for adapting the model parameters. Since state-of-t...
Power consumption has become an increasingly important constraint in high-performancecomputing systems, shifting the focus from peak performance towards improving power efficiency...
Case-based reasoning (CBR) is a knowledge-based problem-solving technique, which is based on reuse of previous experiences. In this paper we propose a new model for static task as...