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Topology-aware navigation in large networks
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Conference on Human Factors in Computing Systems archive
Proceedings of the 27th international conference on Human factors in computing systems table of contents
Boston, MA, USA
SESSION: Understanding graphs table of contents
Pages 2319-2328  
Year of Publication: 2009
ISBN:978-1-60558-246-7
Authors
Tomer Moscovich  Microsoft Research - INRIA Joint Centre, Orsay, France
Fanny Chevalier  Microsoft Research - INRIA Joint Centre, Orsay, France
Nathalie Henry  INRIA, Orsay, France
Emmanuel Pietriga  LRI - Univ. Paris-Sud & CNRS, Orsay, France
Jean-Daniel Fekete  INRIA, Orsay, France
Sponsors
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Applications supporting navigation in large networks are used every days by millions of people. They include road map navigators, flight route visualization systems, and network visualization systems using node-link diagrams. These applications currently provide generic interaction methods for navigation: pan-and-zoom and sometimes bird's eye views.

This article explores the idea of exploiting the connection information provided by the network to help navigate these large spaces. We visually augment two traditional navigation methods, and develop two special-purpose techniques. The first new technique, called "Link Sliding", provides guided panning when continuously dragging along a visible link. The second technique, called "Bring & Go", brings adjacent nodes nearby when pointing to a node. We compare the performance of these techniques in both an adjacency exploration task and a node revisiting task. This comparison illustrates the various advantages of content-aware network navigation techniques. A significant speed advantage is found for the Bring & Go technique over other methods.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Collaborative Colleagues:
Tomer Moscovich: colleagues
Fanny Chevalier: colleagues
Nathalie Henry: colleagues
Emmanuel Pietriga: colleagues
Jean-Daniel Fekete: colleagues