Journal ArticleDOI
Graph visualization and navigation in information visualization: A survey
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TLDR
This is a survey on graph visualization and navigation techniques, as used in information visualization, which approaches the results of traditional graph drawing from a different perspective.Citations
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Proceedings Article
Hierarchical clustering for graph visualization
TL;DR: In this paper, a graph visualization methodology based on hierarchical maximal modularity clustering is described, with interactive and signicant coarsening and rening possibilities, for HIV epidemic analysis in Cuba.
Journal ArticleDOI
Efficient methods and readily customizable libraries for managing complexity of large networks.
Ugur Dogrusoz,Alper Karacelik,Ilkin Safarli,Hasan Balci,Leonard Dervishi,Metin Can Siper,Metin Can Siper +6 more
TL;DR: This work fills an important gap by making efficient implementations of some already known complexity management techniques freely available to tool developers through a couple of open source, customizable software libraries, and by introducing some heuristics which can be applied upon such complexitymanagement techniques to ensure preserving mental map of users.
Proceedings ArticleDOI
Documenting software systems with views III: towards a task-oriented classification of program visualization techniques
Scott Tilley,Shihong Huang +1 more
TL;DR: Preliminary work towards a task-oriented classification of program visualization techniques is described, which divides the visualization techniques into three classes (static, interactive, and editable) based on the level of end-user interaction with the generated graphical documentation.
Book ChapterDOI
Physical navigation to support graph exploration on a large high-resolution display
TL;DR: An approach to visualize a graph hierarchy on a large high-resolution display and to interact with the visualization by physical navigation using head tracking to allow users to explore the graph hierarchy at different levels of abstraction.
Journal ArticleDOI
Multi-Task Learning Based Network Embedding.
TL;DR: This paper proposes a novel method, Multi-Task Learning-Based Network Embedding, termed MLNE, which can obtain node embeddings that can sufficiently reflect the roles that nodes play in networks over existing state-of-the-art methods.
References
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Book
Cluster Analysis
TL;DR: This fourth edition of the highly successful Cluster Analysis represents a thorough revision of the third edition and covers new and developing areas such as classification likelihood and neural networks for clustering.
Journal ArticleDOI
Graph drawing by force-directed placement
TL;DR: A modification of the spring‐embedder model of Eades for drawing undirected graphs with straight edges is presented, developed in analogy to forces in natural systems, for a simple, elegant, conceptually‐intuitive, and efficient algorithm.
Book
Information Visualization: Perception for Design
TL;DR: The art and science of why the authors see objects the way they do are explored, and the author presents the key principles at work for a wide range of applications--resulting in visualization of improved clarity, utility, and persuasiveness.
Journal ArticleDOI
An algorithm for drawing general undirected graphs
Tomihisa Kamada,Satoru Kawai +1 more
Journal ArticleDOI
Generalized fisheye views
TL;DR: This paper explores fisheye views presenting, in turn, naturalistic studies, a general formalism, a specific instantiation, a resulting computer program, example displays and an evaluation.