%0 Conference Paper %1 4272063 %A Bourqui, R. %A Auber, D. %A Mary, P. %B Information Visualization, 2007. IV '07. 11th International Conference %D 2007 %K clustering computergraphics graph multilevel visualization %P 757 -764 %R 10.1109/IV.2007.65 %T How to Draw ClusteredWeighted Graphs using a Multilevel Force-Directed Graph Drawing Algorithm %U http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=4272063&contentType=Conference+Publications&searchField%3DSearch_All%26queryText%3Dbourqui+graph %X Visualization of clustered graphs has been a research area since many years. In this paper, we describe a new approach that can be used in real application where graph does not contain only topological information but also extrinsic parameters (i.e. user attributes on edges and nodes). In the case of force-directed algorithm, management of attributes corresponds to take into account edge weights. We propose an extension of the GRIP algorithm in order to manage edge weights. Furthermore, by using Voronoi diagram we constrained that algorithm to draw each cluster in a non overlapping convex region. Using these two extensions we obtained an algorithm that draw clustered weighted graphs. Experimentation has been done on data coming from biology where the network is the genes- proteins interaction graph and where the attributes are gene expression values from microarray experiments.

@inproceedings{4272063, abstract = {Visualization of clustered graphs has been a research area since many years. In this paper, we describe a new approach that can be used in real application where graph does not contain only topological information but also extrinsic parameters (i.e. user attributes on edges and nodes). In the case of force-directed algorithm, management of attributes corresponds to take into account edge weights. We propose an extension of the GRIP algorithm in order to manage edge weights. Furthermore, by using Voronoi diagram we constrained that algorithm to draw each cluster in a non overlapping convex region. Using these two extensions we obtained an algorithm that draw clustered weighted graphs. Experimentation has been done on data coming from biology where the network is the genes- proteins interaction graph and where the attributes are gene expression values from microarray experiments.}, added-at = {2012-06-01T12:06:26.000+0200}, author = {Bourqui, R. and Auber, D. and Mary, P.}, biburl = {https://www.bibsonomy.org/bibtex/2f8b7ebd31ca216d8556a21fd72eab6e6/rwoz}, booktitle = {Information Visualization, 2007. IV '07. 11th International Conference}, description = {IEEE Xplore - Abstract Page}, doi = {10.1109/IV.2007.65}, interhash = {4cdfe9ec47461d143e6dda850b592c49}, intrahash = {f8b7ebd31ca216d8556a21fd72eab6e6}, issn = {1550-6037}, keywords = {clustering computergraphics graph multilevel visualization}, month = {july}, pages = {757 -764}, timestamp = {2012-06-01T12:06:26.000+0200}, title = {How to Draw ClusteredWeighted Graphs using a Multilevel Force-Directed Graph Drawing Algorithm}, url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=4272063&contentType=Conference+Publications&searchField%3DSearch_All%26queryText%3Dbourqui+graph}, year = 2007 }