Knowledge discovery systems extract knowledge from data that can be used for making prediction about incomplete data items. Utility is a measure of the usefulness of the discovere...
We present a Semantic Optimized Service Discovery (SemOSD) approach capable of handling Web service search requests on a fine-grained level of detail where we augment semantic ser...
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
—Scheduling task graphs under hard (end-to-end) timing constraints is an extensively studied NP-hard problem of critical importance for predictable software mapping on Multiproce...
The assessment of routing protocols for wireless networks is a difficult task, because of the networks’ highly dynamic behavior and the absence of benchmarks. However, some of ...