The recent years have witnessed a surge of interests of semi-supervised clustering methods, which aim to cluster the data set under the guidance of some supervisory information. U...
Most data integration applications require a matching between the schemas of the respective data sets. We show how the existence of duplicates within these data sets can be exploi...
Clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity classes. This p...
Much work in AI deals with the selection of proper actions in a given (known or unknown) environment. However, the way to select a proper action when facing other agents is quite ...
— Scientific applications often perform complex computational analyses that consume and produce large data sets. We are concerned with data placement policies that distribute dat...
Ann L. Chervenak, Ewa Deelman, Miron Livny, Mei-Hu...