We present a theoretical analysis of Watson’s Hierarchicalif-and-only-if (HIFF) problem using a variety of tools. These include schema theory and course graining, the concept of...
Clustering, in data mining, is useful to discover distribution patterns in the underlying data. Clustering algorithms usually employ a distance metric based (e.g., euclidean) simi...
In order to overcome the limitations of deductive logic-based approaches to deriving operational knowledge from ontologies, especially when data come from distributed sources, indu...
Social networks are of interest to researchers in part because they are thought to mediate the flow of information in communities and organizations. Here we study the temporal dyn...
Gueorgi Kossinets, Jon M. Kleinberg, Duncan J. Wat...
Often several cooperating parties would like to have a global view of their joint data for various data mining objectives, but cannot reveal the contents of individual records due...