2,428 research outputs found
Visualization of Co-authorshipin DIT Arrow
With the popularization of information technology and the unprecedented development of online reading, the management and service of the library are facing severe challenges; the traditional library operation mode has been challenging to optimize the service. At the same time, there is also a fatal impact on library collection and systematic management, however, with the development of visualization techniques in management and service, the library can alleviate the eļ¬ect of the current network information basically, which achieves the intellectual development of library ļ¬eld. This study empirically provides the evidence to indicate that the force directed layout has the statistically signiļ¬cant performance than the radial layout for visualization of co-authorship in DIT Arrow repository based on the results of surveys
Graph Layout Performance Comparisons of Force-Directed Algorithms
Ā© 2018 Totem Publisher, Inc. All rights reserved. Due to force-directed algorithmsā capabilities of producing aesthetically pleasing graph layouts, which follow metrics for graph drawing aesthetics, these layouts have become the most common methods in the practical data visualization area. However, evaluating the performance of relevant algorithms remains a challenge, since graph layout quality is largely relying on aspects such as human intuition, personal judgment and methodsā pre-setting parameters. In addition, most aesthetics criteria of graph drawing conflict with each other. This study evaluated the performance measurements of four force-directed algorithms in terms of seven commonly applied aesthetic criteria based on practical raw data collected, and demonstrated the experimental framework. The early outcomes compared twenty final graph layouts and gave empirical evidences; the study may assist with future detailed force-directed algorithms selection based on usersā specific requirements
Scalability considerations for multivariate graph visualization
Real-world, multivariate datasets are frequently too large to show in their entirety on a visual display. Still, there are many techniques we can employ to show useful partial views-sufficient to support incremental exploration of large graph datasets. In this chapter, we first explore the cognitive and architectural limitations which restrict the amount of visual bandwidth available to multivariate graph visualization approaches. These limitations afford several design approaches, which we systematically explore. Finally, we survey systems and studies that exhibit these design strategies to mitigate these perceptual and architectural limitations
A Coloring Algorithm for Disambiguating Graph and Map Drawings
Drawings of non-planar graphs always result in edge crossings. When there are
many edges crossing at small angles, it is often difficult to follow these
edges, because of the multiple visual paths resulted from the crossings that
slow down eye movements. In this paper we propose an algorithm that
disambiguates the edges with automatic selection of distinctive colors. Our
proposed algorithm computes a near optimal color assignment of a dual collision
graph, using a novel branch-and-bound procedure applied to a space
decomposition of the color gamut. We give examples demonstrating the
effectiveness of this approach in clarifying drawings of real world graphs and
maps
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