In processing discrete-choice spatially referenced data evolving from large hierarchical structures, investigators typically encounter three imposing difficulties. One difficulty is the evaluation of a large-scale determinant resulting from the Jacobian of the transformation from the error structure to the latent variables used to simulate the discrete choices. A second difficulty results from ...

In the paper we investigate stochastic local search by Markov chain analysis in a high and a low dimensional discrete space. In the n-dimensional space Bn a function called Jump is considered. The analysis shows that an algorithm using a large neighborhood and never accepting worse points performs much better than any local search algorithm accepting worse points with a certain probability. We ...

The Internet provides easy access to a kind of library resources. However, classification of documents from a large amount of data is still an issue and demands time and energy to find certain documents. Classification of similar documents in specific classes of data can reduce the time for searching the required data, particularly text documents. This is further facilitated by using Artificial...

Abstract With the prevalence of Internet access and online services, various big graphs are generated in many real applications (e.g., social networks knowledge graphs). An important task on analyzing mining these is keyword search. Essentially, given a graph G query Q associated with set keywords, search aims to find substructure rooted tree or subgraph) S such that nodes collectively cover pa...

In remote sensing image-blurring is induced by many sources such as atmospheric scatter, optical aberration, spatial and temporal sensor integration. The natural blurring can be exploited to speed up target search by fast template matching. In this paper, we synthetically induce additional non-uniform blurring to further increase the speed of the matching process. To avoid loss of accuracy, the...