Abstract. Novelty detection in data stream mining denotes the identification of new or unknown situations in a stream of data elements flowing continuously in at rapid rate. This...
Efficient memory allocation and data transfer for cluster-based data-intensive applications is a difficult task. Both changes in cluster interconnects and application workloads ...
—Modern large-scale grid computing for processing advanced science and engineering applications relies on geographically distributed clusters. In such highly distributed environm...
Daniel M. Batista, Luciano Chaves, Nelson L. S. da...
The training of Emergent Self-organizing Maps (ESOM ) with large datasets can be a computationally demanding task. Batch learning may be used to speed up training. It is demonstrat...
: Appraisal of companies is an important business activity. We mainly apply Bayesian networks for this classification task for Japanese electric company data. Firstly, few standard...