visual analytics has the potential to circumvent this real-time information overload by combining incremental analy-sis algorithms and visualizations to facilitate data stream analysis and provide situa-tional awareness. In this book chapter we will thus define dynamic visual analytics, discuss its key

on a factor graph can be embedded in a network of spiking neurons. We use pools of spiking neurons as the function nodes of the factor graph. Each pool gathers ’messages ’ in the form of population activities from its input nodes and combines them through its network dynamics. The various output

reinventing the nature of the threat. Anticipating attacks through behavior analysis is potentially confounded by the data sources and patterns which are relevant to the analysis changing regularly, forcing security agencies around to continually adapt their data sources and analytic methods in the pursuit

visual analysis on multivariate tabular data. Powered by an underlying relational algebraic framework, Ploceus supports flexible construction and transformation of networks through a direct manipulation interface, and integrates dynamic network manipulation with visual exploration for a seamless analytic

. The number of factors is treated as another unknown parameter and fully Bayesian inference is performed via a reversible jump Markov Chain Monte Carlo algorithm. The new class of models is tested against one synthetic dataset and applied to pollution data obtained from the Clean Air Status and Trends Network

as conversations with the domain expert, we demonstrate the effectiveness of the EgoNetCloud design and system in com-pleting analysis tasks on event-based dynamic networks. The user study comparing EgoNetCloud with a working system on academic search confirms the effectiveness and convenience of our visual an-alytics

algorithm over the baseline method. Keywords social network analysis, dynamic network visualization, community detection, evolutionary clustering 1.

Abstract This paper evaluates the performance of a context discovery protocol using attenuated Bloom filters while nodes appear, disappear, and are temporary unreachable in ad-hoc networks through analytical analysis. Further we verified ob-tained results with simulation analysis. The analytical

, qualitative subgraph extraction through a novel 2D user interface, quantitative subgraph extraction using graph-theoretic algorithms or by querying an optimized b-tree, dynamic level-of-detail graph abstraction, and template-based fuzzy classification using neural networks. We demonstrate our system using a

We introduce a new visual analytic approach to the study of scientific discoveries and knowledge diffusion. Our approach enhances contemporary co-citation network analysis by enabling analysts to identify co-citation clusters of cited references intuitively, synthesize thematic contexts in which