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.
Description
IEEE Xplore Abstract - Embedding, clustering and coloring for dynamic maps
%0 Conference Paper
%1 hu2012embedding
%A Hu, Yifan
%A Kobourov, S.G.
%A Veeramoni, S.
%B Visualization Symposium (PacificVis), 2012 IEEE Pacific
%D 2012
%K drawing dynamic graph map topoi
%P 33-40
%R 10.1109/PacificVis.2012.6183571
%T Embedding, clustering and coloring for dynamic maps
%U http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6183571
%X 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.
@inproceedings{hu2012embedding,
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.},
added-at = {2015-10-22T19:29:42.000+0200},
author = {Hu, Yifan and Kobourov, S.G. and Veeramoni, S.},
biburl = {https://www.bibsonomy.org/bibtex/29f6c94b309991ff72c061a4b6c6737bd/stumme},
booktitle = {Visualization Symposium (PacificVis), 2012 IEEE Pacific},
description = {IEEE Xplore Abstract - Embedding, clustering and coloring for dynamic maps},
doi = {10.1109/PacificVis.2012.6183571},
interhash = {64b61421c989bbceeece856b759f007a},
intrahash = {9f6c94b309991ff72c061a4b6c6737bd},
issn = {2165-8765},
keywords = {drawing dynamic graph map topoi},
month = feb,
pages = {33-40},
timestamp = {2015-10-22T19:29:42.000+0200},
title = {Embedding, clustering and coloring for dynamic maps},
url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6183571},
year = 2012
}