In this paper, we propose a novel memory-based collaborative filtering recommendation algorithm. Our algorithm use a new metric named influence weight, which is adjusted with ze...
This paper proposes the integration of semantic information drawn from a web application’s domain knowledge into all phases of the web usage mining process (preprocessing, patte...
This paper discusses the combination of collaborative and contentbased filtering in the context of web-based recommender systems. In particular, we link the well-known MovieLens ...
Subgroup discovery is a Knowledge Discovery task that aims at finding subgroups of a population with high generality and distributional unusualness. While several subgroup discove...
We consider causally sufficient acyclic causal models in which the relationship among the variables is nonlinear while disturbances have linear effects, and show that three princi...