Knowledge engineering techniques are becoming useful and popular components of hybrid integrated systems used to solve complicated practical problems in different fields. Knowledge...
Methods for discovering causal knowledge from observational data have been a persistent topic of AI research for several decades. Essentially all of this work focuses on knowledge...
Marc Maier, Brian Taylor, Huseyin Oktay, David Jen...
Today's data networks are surprisingly fragile and difficult to manage. We argue that the root of these problems lies in the complexity of the control and management planes--...
Practical knowledge discovery is an iterative process. First, the experiences gained from one mining run are used to inform the parameter setting and the dataset and attribute sel...
Knowledge discovery allows considerable insight into data. This brings with it the inherent risk that what is inferred may be private or ethically sensitive. The process of genera...