Force-directed algorithms for schematic drawings and placement: A survey

Cheong, Se-Hang; Si, Yain-Whar

doi:10.1177/1473871618821740

Cited by 28 publications

(21 citation statements)

References 171 publications

(211 reference statements)

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“…Among notable forcedirected graph drawing algorithms, [43] and [44] have been most influential. A survey of different force-directed algorithms can be found in [45]. A quite similar concept is force-directed data projection techniques such as force scheme [24] where the biggest difference is the goal of techniques and usage of distances in original space and the possibility of not having a graph at all.…”

Section: Related Workmentioning

confidence: 99%

Multi-point dimensionality reduction to improve projection layout reliability

Barahimi¹

2021

Preprint

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In ordinary Dimensionality Reduction (DR), each data instance in an m-dimensional space (original space) is mapped to one point in a d-dimensional space (visual space), preserving as much as possible distance and/or neighborhood relationships. Despite their popularity, even for simple datasets, the existing DR techniques unavoidably may produce misleading visual representations. The problem is not with the existing solutions but with problem formulation. For two dimensional visual space, if data instances are not co-planar or do not lie on a 2D manifold, there is no solution for the problem, and the possible approximations usually result in layouts with inaccuracies in the distance preservation and overlapped neighborhoods. In this paper, we elaborate on the concept of Multi-point Dimensionality Reduction where each data instance can be mapped to possibly more than one point in the visual space by providing the first general solution to it as a step toward mitigating this issue. By duplicating points, background information is added to the visual representation making local neighborhoods in the visual space more faithful to the original space. Our solution, named Red Gray Plus, is built upon and extends a combination of ordinary DR and graph drawing techniques. We show that not only Multi-point Dimensionality Reduction can be one of the potential directions to improve DR layouts' reliability but also that our initial solution to the problem outperforms popular ordinary DR methods quantitatively.

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Section: Related Workmentioning

confidence: 99%

Multi-point dimensionality reduction to improve projection layout reliability

Barahimi¹

2021

Preprint

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“…Two-dimensional (2D) graph drawing methods have been broadly reported in textbooks and surveys [5,24,59]. Force-directed and related drawing methods are classified into three categories [24]: forcedirected methods, dimension-reduction methods, and multi-level methods.…”

Section: Graph Visualizationmentioning

confidence: 99%

“…Generating appropriate layouts of graph data has been a major research topic over the past decades, as witnessed by the extensive literature [5,12,24,30,59]. Among many solutions, node-link diagrams are widely used, because they reveal topology and connectivities [23].…”

Section: Introductionmentioning

confidence: 99%

Exemplar-based Layout Fine-tuning for Node-link Diagrams

Pan

Chen

Zhao

et al. 2020

Preprint

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“…Research on the graph drawing is known for its force-directed model, and various versions have been developed to improve the layout quality. Force-directed model follows the simulation of a spring system, in which the length of the spring is proportional to the force exerted by an extended spring [19]. The first force-directed model was originally proposed by Eades [20].…”

Section: B Graph Layout Algorithmmentioning

confidence: 99%

IES-Backbone: An Interactive Edge Selection Based Backbone Method for Small World Network Visualization

et al. 2019

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Visualization of the small world network is an excellent challenge for classic layout algorithm, which is highly connected, resulting in the shape of the hairball. Backbone extraction method can simplify the classic layout to get better visualization, and it has become a significant approach in this field. However, contemporary approaches have two primary defects. Centrality based method loses plenty of topology information, and most contemporary approaches have the problem in low interactivity due to parameter sensibility. We proposed a backbone method based on interactive edge selection (IES-Backbone) to solve two problems for small world network visualization that mentioned above. The proposed method starts with backbone extraction of the network and then apply the layout algorithm to get visualization results. A critical approach of the backbone method is edge selection, which is based on the distance between vertices layout of the binary stress model. Edge selection makes the simplified network a clear community structure feature with more topological details. The simplified network is high in homophily and has closer average path length to the original network. The visualization result is controlled by edge limit ratio r and sampling rate s. Different choices of two parameters can change the results substantially on visual without affecting the layout quality, which proves high interactivity for users. Experiments prove that IES-Backbone is an interactive visualization method that presents community and sufficient topological features. INDEX TERMS Visualization, graph layout, small world network, backbone.

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Force-directed algorithms for schematic drawings and placement: A survey

Cited by 28 publications

References 171 publications

Multi-point dimensionality reduction to improve projection layout reliability

Multi-point dimensionality reduction to improve projection layout reliability

Exemplar-based Layout Fine-tuning for Node-link Diagrams

IES-Backbone: An Interactive Edge Selection Based Backbone Method for Small World Network Visualization

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