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Journal ArticleDOI

Graph visualization and navigation in information visualization: A survey

Ivan Herman, +2 more
- 01 Jan 2000 - 
- Vol. 6, Iss: 1, pp 24-43
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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.
Abstract
This is a survey on graph visualization and navigation techniques, as used in information visualization. Graphs appear in numerous applications such as Web browsing, state-transition diagrams, and data structures. The ability to visualize and to navigate in these potentially large, abstract graphs is often a crucial part of an application. Information visualization has specific requirements, which means that this survey approaches the results of traditional graph drawing from a different perspective.

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Concept maps for designing adaptive knowledge maps

TL;DR: This paper presents both a method, called ‘Domain-View-Controller’ (DVC) and a software environment specifically designed to create adaptive KMaps from CMaps, giving end users the ability to display complex knowledge without having the expertise of knowledge engineers.
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Visualising larger state spaces in ProB

TL;DR: Two relatively simple algorithms are presented to often considerably reduce the complexity of the graphs, while still keeping relevant information and this makes it possible to visualise much larger state spaces and gives the user immediate feedback about the overall behaviour of a machine.
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Visualizing Semantic Web proofs of defeasible logic in the DR-DEVICE system

TL;DR: A fourth, hybrid visualization approach that combines the pros of all three approaches and attempts to leverage the respective cons is proposed and a software tool is presented that implements the proposed hybrid approach.
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Visualization of variability and configuration options

TL;DR: This paper provides concepts for interactive visual tool support for the configuration of systems with the help of feature models by discussing relevant principles from the area of information visualization and their application to the domain of feature model configuration.
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Employing artificial neural networks for constructing metadata-based model to automatically select an appropriate data visualization technique

TL;DR: The results show that the proposed Display Omitted Solution assists in selecting an appropriate visualization technique for a given dataset with high accuracy.
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

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.