Visual Recommendations for Network Navigation
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Date
2011
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and Blackwell Publishing Ltd.
Abstract
Understanding large, complex networks is important for many critical tasks, including decision making, process optimization, and threat detection. Existing network analysis tools often lack intuitive interfaces to support the exploration of large scale data. We present a visual recommendation system to help guide users during navigation of network data. Collaborative filtering, similarity metrics, and relative importance are used to generate recommendations of potentially significant nodes for users to explore. In addition, graph layout and node visibility are adjusted in real-time to accommodate recommendation display and to reduce visual clutter. Case studies are presented to show how our design can improve network exploration.
Description
@article{:10.1111/j.1467-8659.2011.01957.x,
journal = {Computer Graphics Forum},
title = {{Visual Recommendations for Network Navigation}},
author = {Crnovrsanin, Tarik and Liao, Isaac and Wuy, Yingcai and Ma, Kwan-Liu},
year = {2011},
publisher = {The Eurographics Association and Blackwell Publishing Ltd.},
ISSN = {1467-8659},
DOI = {/10.1111/j.1467-8659.2011.01957.x}
}