A hybrid space-filling and force-directed layout method for visualizing multiple-category graphs

Takayuki Itoh; Chris Muelder; Kwan-Liu Ma; Jun Sese

doi:10.1109/PACIFICVIS.2009.4906846

A hybrid space-filling and force-directed layout method for visualizing multiple-category graphs

Takayuki Itoh, Chris Muelder, Kwan-Liu Ma, Jun Sese

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

40 Scopus citations

Abstract

Many graphs used in real-world applications consist of nodes belonging to more than one category. We call such graph "multiplecategory graphs". Social networks are typical examples of multiplecategory graphs: nodes are persons, links are friendships, and categories are communities that the persons belong to. It is often helpful to visualize both connectivity and categories of the graphs simultaneously. In this paper, we present a new visualization technique for multiple-category graphs. The technique firstly constructs hierarchical clusters of the nodes based on both connectivity and categories. It then places the nodes by a new hybrid space-filling and force-directed layout algorithm to clearly display both connectivity and category information. We show layout results using our hybrid method and compare it with other methods, and present a case study using an active biological network dataset.

Original language	English (US)
Title of host publication	IEEE Pacific Visualization Symposium, PacificVis 2009 - Proceedings
Pages	121-128
Number of pages	8
DOIs	https://doi.org/10.1109/PACIFICVIS.2009.4906846
State	Published - Jul 21 2009
Event	IEEE Pacific Visualization Symposium, PacificVis 2009 - Beijing, China Duration: Apr 20 2009 → Apr 23 2009

Other

Other	IEEE Pacific Visualization Symposium, PacificVis 2009
Country	China
City	Beijing
Period	4/20/09 → 4/23/09

Keywords

Active biological network
Clustering
Force directed layout
Graph visualization
Information visualization
Multiple-category graphs
Space-filling hierarchical data visualization

ASJC Scopus subject areas

Computer Graphics and Computer-Aided Design
Computer Vision and Pattern Recognition
Software

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10.1109/PACIFICVIS.2009.4906846

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Cite this

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title = "A hybrid space-filling and force-directed layout method for visualizing multiple-category graphs",

abstract = "Many graphs used in real-world applications consist of nodes belonging to more than one category. We call such graph {"}multiplecategory graphs{"}. Social networks are typical examples of multiplecategory graphs: nodes are persons, links are friendships, and categories are communities that the persons belong to. It is often helpful to visualize both connectivity and categories of the graphs simultaneously. In this paper, we present a new visualization technique for multiple-category graphs. The technique firstly constructs hierarchical clusters of the nodes based on both connectivity and categories. It then places the nodes by a new hybrid space-filling and force-directed layout algorithm to clearly display both connectivity and category information. We show layout results using our hybrid method and compare it with other methods, and present a case study using an active biological network dataset.",

keywords = "Active biological network, Clustering, Force directed layout, Graph visualization, Information visualization, Multiple-category graphs, Space-filling hierarchical data visualization",

author = "Takayuki Itoh and Chris Muelder and Kwan-Liu Ma and Jun Sese",

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AU - Muelder, Chris

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AU - Sese, Jun

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AB - Many graphs used in real-world applications consist of nodes belonging to more than one category. We call such graph "multiplecategory graphs". Social networks are typical examples of multiplecategory graphs: nodes are persons, links are friendships, and categories are communities that the persons belong to. It is often helpful to visualize both connectivity and categories of the graphs simultaneously. In this paper, we present a new visualization technique for multiple-category graphs. The technique firstly constructs hierarchical clusters of the nodes based on both connectivity and categories. It then places the nodes by a new hybrid space-filling and force-directed layout algorithm to clearly display both connectivity and category information. We show layout results using our hybrid method and compare it with other methods, and present a case study using an active biological network dataset.

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