force-directed algorithms have been developed over the last 50 years and used in many application fields, including information visualisation, biological network visualisation, sensor networks, routing algorithms, sch...
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force-directed algorithms have been developed over the last 50 years and used in many application fields, including information visualisation, biological network visualisation, sensor networks, routing algorithms, scheduling, and graph drawing. Our survey provides a comprehensive summary of developments and a full roadmap for state-of-the-art force-directed algorithms in schematic drawings and placement. We classified the model of force-directed algorithms into classical and hybrid. The classical force-directed algorithms are further classified as follows: (a) accumulated force models, (b) energy function minimisation models and (c) combinatorial optimisation models. The hybrid force-directed algorithms are classified as follows: (a) parallel and hardware accelerated models, (b) multilevel force-directed models and (c) multidimensional scaling force-directed algorithms. Five categories of application domains in which force-directed algorithms have been adopted for schematic drawings and placement are also summarised: (a) aesthetic drawings for general networks, (b) component placement and scheduling in high-level synthesis of very-large-scale integration circuits design, (c) information visualisation, (d) biological network visualisation and (e) node placement and localisation for sensor networks.
force-directed (FD) algorithms can be used to explore relationships in social networks, visualize money markets, and analyze transaction networks. However, FD algorithms are mainly designed for visualizing static grap...
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force-directed (FD) algorithms can be used to explore relationships in social networks, visualize money markets, and analyze transaction networks. However, FD algorithms are mainly designed for visualizing static graphs in which the topology of the networks remains constant throughout the calculation. In contrast to static graphs, nodes and edges in dynamic graphs can be added or removed as time progresses. In these situations, existing FD algorithms do not scale well, since any changes in the topology will trigger these algorithms to completely restart the entire computation. To alleviate this problem, we propose a design and implementation of five online FD algorithms to visualize dynamic graphs while maintaining their native force models. The online FD algorithms developed in this paper are able to reuse the force models of existing FD algorithms without significant modifications. To evaluate the effectiveness of the proposed approach, online FD algorithms are compared against static FD algorithms for visualizing dynamic graphs. Experimental results show that among the five algorithms evaluated, the online FD algorithm achieves the best number of edge crossings and the standard deviation of edge lengths for visualizing dynamic graphs. (C) 2021 Elsevier Inc. All rights reserved.
force-directed algorithms are widely used for visualizing graphs. However, these algorithms are computationally expensive in producing good quality layouts for complex graphs. The layout quality is largely influenced ...
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ISBN:
(纸本)9781538691250
force-directed algorithms are widely used for visualizing graphs. However, these algorithms are computationally expensive in producing good quality layouts for complex graphs. The layout quality is largely influenced by execution time and methods' input parameters especially for large complex graphs. The snapshots of visualization generated from these algorithms are useful in presenting the current view or a past state of an information on timeslices. Therefore, researchers often need to make a trade-off between the quality of visualization and the selection of appropriate force-directed algorithms. In this paper, we evaluate the quality of snapshots generated from 7 force-directed algorithms in terms of number of edge crossing and the standard deviations of edge length. Our experimental results showed that KK, FA2 and DH algorithms cannot produce satisfactory visualizations for large graphs within the time limit. KK-MS-DS algorithm can process large and planar graphs but it does not perform well for graphs with low average degrees. KK-MS algorithm produces better visualizations for sparse and non-clustered graphs than KK-MS-DS algorithm.
Evaluation on the performance of relevant force-directed algorithms is still a challenge, since layout quality is largely relying on personal judgement and/or methods' input parameters, and most aesthetics criteri...
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ISBN:
(纸本)9781538626368
Evaluation on the performance of relevant force-directed algorithms is still a challenge, since layout quality is largely relying on personal judgement and/or methods' input parameters, and most aesthetics criteria conflict with each other. This study conducts the performance measurements of four algorithms in terms of seven commonly applied aesthetic criteria and demonstrates the experimental framework.
Real-world networks show community structures - groups of nodes that are densely intraconnected and sparsely inter-connected to other groups. Nevertheless, Community Detection (CD) is non-trivial, since identifying th...
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Real-world networks show community structures - groups of nodes that are densely intraconnected and sparsely inter-connected to other groups. Nevertheless, Community Detection (CD) is non-trivial, since identifying these groups of nodes according to their local connectivity can hold many plausible solutions, leading to the creation of different methods. In particular, CD has recently been achieved by force-directed algorithms (FDAs), which originally were designed as a way to visualize networks. FDAs map the network nodes as particles in a D-dimensional space that are affected by forces acting in accordance to the connectivity. However, the literature on FDA-based methods for CD has grown in parallel from the classical methods, leaving several open questions, such as how accurately FDAs can recover communities compared to classical methods. In this work, we start to fill these gaps by evaluating different numerical implementations of 5 FDA methods and different clustering analyses on state-of-the-art network benchmarks - including networks with or without weights and networks with a hierarchical organisation. We also compare these results with 8, well-known, classical CD methods. Our findings show that FDA methods can achieve higher accuracy than classical methods, albeit their effectiveness depends on the chosen setting - with optimisation techniques leading over numerical integration and distance-based clustering algorithms leading over density-based ones. Overall, our work provides detailed information for any researcher aiming to apply FDAs for community detection. (C) 2022 Elsevier Inc. All rights reserved.
Recent works in graph visualization attempt to reduce the runtime of repulsion force computation of force-directed algorithms using sampling. However, they fail to reduce the runtime for attraction force computation t...
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Recent works in graph visualization attempt to reduce the runtime of repulsion force computation of force-directed algorithms using sampling. However, they fail to reduce the runtime for attraction force computation to sublinear in the number of edges. We present the SubLinearforce framework for a fully sublinear-time force computation algorithm for drawing large complex graphs. More precisely, we present new sublinear-time algorithms for the attraction force computation of force-directed algorithms. We then integrate them with sublinear-time repulsion force computation to give a fully sublinear-time force computation. Extensive experiments show that our algorithms compute layouts on average 80% faster than the existing linear-time force computation algorithm, while obtaining significantly better quality metrics such as edge crossing and shape-based metrics.
We present a novel algorithm to match GPS trajectories onto maps offline (in batch mode) using techniques borrowed from the field of force-directed graph drawing. We consider a simulated physical system where each GPS...
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ISBN:
(纸本)9781450358897
We present a novel algorithm to match GPS trajectories onto maps offline (in batch mode) using techniques borrowed from the field of force-directed graph drawing. We consider a simulated physical system where each GPS trajectory is attracted or repelled by the underlying road network via electrical-like forces. We let the system evolve under the action of these physical forces such that individual trajectories are attracted towards candidate roads to obtain a map matching path. Our approach has several advantages compared to traditional, routing-based, algorithms for map matching, including the ability to account for noise and to avoid large detours due to outliers in the data whilst taking into account the underlying topological restrictions (such as one-way roads). Our empirical evaluation using real GPS traces shows that our method produces better map matching results compared to alternative offline map matching algorithms on average, especially for routes in dense, urban areas.
As a formal description approach, the trust network can intuitively describe trust relationships among entities in virtual communities and attracts great attentions. The trust network visualization is a key to explore...
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ISBN:
(纸本)9780769551340
As a formal description approach, the trust network can intuitively describe trust relationships among entities in virtual communities and attracts great attentions. The trust network visualization is a key to explore the mechanism of trust propagation and study the trust evaluation. Most existing network visualization approaches only take into account the undirected and unweighted graphs, which cannot illustrate the asymmetry and the discreteness of trust relationships. To solve this issue, we define the public influence weight, the trust strength and the trust distance in this paper and propose the force-directed visualization algorithm for trust network. In the visualization algorithm, the desirable length between two nodes is determined by the trust strength so as to cluster trusted entities, and the forces between two different nodes are determined by their public influence weights so as to center on the heavyweight entities. Finally, the visualization experiments are carried out on the Epinions data set and the performance of the proposed algorithm is compared with the classical force-directed layout algorithm. The experimental results show that it can reveal the nature of communities better.
In this paper we discuss a useful family of graph drawing algorithms, characterized by their ability to draw graphs in one dimension. We define the special requirements from such algorithms and show how several graph ...
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In this paper we discuss a useful family of graph drawing algorithms, characterized by their ability to draw graphs in one dimension. We define the special requirements from such algorithms and show how several graph drawing techniques can be extended to handle this task. In particular, we suggest a novel optimization algorithm that facilitates using the Kamada and Kawai model [Inform. Process. Lett. 31 (1989) 7-15] for producing one-dimensional layouts. The most important application of the algorithms seems to be in achieving graph drawing by axis separation, where each axis of the drawing addresses different aspects of aesthetics. (c) 2005 Elsevier B.V. All rights reserved.
We present a conceptually simple approach to generalizing force-directed methods for graph layout from Euclidean geometry to Riemannian geometries. Unlike previous work on non-Euclidean force-directed methods, ours is...
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We present a conceptually simple approach to generalizing force-directed methods for graph layout from Euclidean geometry to Riemannian geometries. Unlike previous work on non-Euclidean force-directed methods, ours is not limited to special classes of graphs, but can be applied to arbitrary graphs. The method relies on extending the Euclidean notions of distance, angle, and force-interactions to smooth non-Euclidean geometries via projections to and from appropriately chosen tangent spaces. In particular, we formally describe the calculations needed to extend such algorithms to hyperbolic and spherical geometries. We also study the theoretical and practical considerations that arise when working with non-Euclidean geometries.
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