High-level stochastic description methods such as stochastic Petri nets, stochastic UML statecharts etc., together with specifications of performance variables (PVs), enable a co...
This paper introduces LDA-G, a scalable Bayesian approach to finding latent group structures in large real-world graph data. Existing Bayesian approaches for group discovery (suc...
Collective operations on distributed data sets foster a high-level data-parallel programming style that eases many aspects of parallel programming significantly. In this paper we...
The performance of information retrieval on the Web is heavily influenced by the organization of Web pages, user navigation patterns, and guidance-related functions. Having observ...
—Normalization before clustering is often needed for proximity indices, such as Euclidian distance, which are sensitive to differences in the magnitude or scales of the attribute...