Visual Recommendations for Network Navigation

dc.contributor.authorCrnovrsanin, Tariken_US
dc.contributor.authorLiao, Isaacen_US
dc.contributor.authorWuy, Yingcaien_US
dc.contributor.authorMa, Kwan-Liuen_US
dc.contributor.editorH. Hauser, H. Pfister, and J. J. van Wijken_US
dc.date.accessioned2014-02-21T20:23:52Z
dc.date.available2014-02-21T20:23:52Z
dc.date.issued2011en_US
dc.description.abstractUnderstanding 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.en_US
dc.description.number3en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume30en_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2011.01957.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.subject[Visual Knowledge Discovery]en_US
dc.subjectData Filteringen_US
dc.subjectGraph/Network Dataen_US
dc.subjectHumanen_US
dc.subjectComputer Interactionen_US
dc.titleVisual Recommendations for Network Navigationen_US
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