This paper describes a novel approach for obtaining semantic interoperability among data sources in a bottom-up, semiautomatic manner without relying on pre-existing, global seman...
Karl Aberer, Manfred Hauswirth, Philippe Cudr&eacu...
Spatial classification is the task of learning models to predict class labels based on the features of entities as well as the spatial relationships to other entities and their fe...
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Nearest neighbor (NN) search in high dimensional space is an important problem in many applications. Ideally, a practical solution (i) should be implementable in a relational data...
A primary challenge to large-scale data integration is creating semantic equivalences between elements from different data sources that correspond to the same real-world entity or...
Shawn R. Jeffery, Michael J. Franklin, Alon Y. Hal...