A clustering method is presented which can be applied to knowledge bases storing semantically annotated resources. The method can be used to discover groupings of structured objec...
In data warehousing applications, the ability to efficiently delete large chunks of data from a table is very important. This feature is also known as Rollout. Rollout is generall...
This paper addresses the problem of scheduling parallel tasks, represented by a direct acyclic graph (DAG) on heterogeneous clusters. Parallel tasks, also called malleable tasks, ...
Jorge G. Barbosa, C. N. Morais, R. Nobrega, A. P. ...
Semi-supervised learning methods construct classifiers using both labeled and unlabeled training data samples. While unlabeled data samples can help to improve the accuracy of trai...
Multidimensional aggregation queries constitute the single most important class of queries for data warehousing applications and decision support systems. The bottleneck in the ev...