Standard financial techniques neglect extreme situations and regards large market shifts as too unlikely to matter. Such approach accounts for what occurs most of the time in the ...
Antoaneta Serguieva, John Hunter, Tatiana Kalganov...
This paper presents approaches for building, managing, and evaluating consensus ontologies from the individual ontologies of a network of socially interacting agents. Each agent h...
Large-scale N-body simulations play an important role in advancing our understanding of the formation and evolution of large structures in the universe. These computations require ...
Traditionally, information extraction from web tables has focused on small, more or less homogeneous corpora, often based on assumptions about the use of <table> tags. A mul...
We propose a new approach for learning Bayesian classifiers from data. Although it relies on traditional Bayesian network (BN) learning algorithms, the effectiveness of our approa...