Embedding, clustering and coloring for dynamic maps

Yifan Hu, Stephen G. Kobourov, Sankar Veeramoni

Research output: Chapter in Book/Report/Conference proceedingConference contribution

24 Scopus citations

Abstract

We describe a practical approach for visualizing multiple relationships defined on the same dataset using a geographic map metaphor, where clusters of nodes form countries and neighboring countries correspond to nearby clusters. Our aim is to provide a visualization that allows us to compare two or more such maps (showing an evolving dynamic process, or obtained using different relationships). In the case where we are considering multiple relationships, e.g., different similarity metrics, we also provide an interactive tool to visually explore the effect of combining two or more such relationships. Our method ensures good readability and mental map preservation, based on dynamic node placement with node stability, dynamic clustering with cluster stability, and dynamic coloring with color stability.

Original languageEnglish (US)
Title of host publicationIEEE Pacific Visualization Symposium 2012, PacificVis 2012 - Proceedings
Pages33-40
Number of pages8
DOIs
StatePublished - 2012
Event5th IEEE Pacific Visualization Symposium 2012, PacificVis 2012 - Songdo, Korea, Republic of
Duration: Feb 28 2012Mar 2 2012

Publication series

NameIEEE Pacific Visualization Symposium 2012, PacificVis 2012 - Proceedings

Other

Other5th IEEE Pacific Visualization Symposium 2012, PacificVis 2012
CountryKorea, Republic of
CitySongdo
Period2/28/123/2/12

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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    Hu, Y., Kobourov, S. G., & Veeramoni, S. (2012). Embedding, clustering and coloring for dynamic maps. In IEEE Pacific Visualization Symposium 2012, PacificVis 2012 - Proceedings (pp. 33-40). [6183571] (IEEE Pacific Visualization Symposium 2012, PacificVis 2012 - Proceedings). https://doi.org/10.1109/PacificVis.2012.6183571