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Published Articles >> Table of Contents >> Abstract
Seventh International Conference on Information Visualization (IV'03)
p. 576
Semantically Modified Diffusion Limited Aggregation for Visualizing Large-Scale Networks
Chaomei Chen, Drexel University
Natasha Lobo, Drexel University
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IV.2003.1218043
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| Abstract |
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Diffusion-Limited Aggregation (DLA) is a model of fractal growth. Computer models can simulate the fast aggregation of millions of particles. In this paper, we propose a modified version of DLA, called semantically modified DLA (SM-DLA), for visualizing large-scale networks. SM-DLA introduces similarity measures between particles so that instead of attaching to the nearest particle in the aggregation, a new particle is stochastically directed to attach to particles that are similar to it. The results of our initial experiment with a co-citation network using SM-DLA are encouraging, suggesting that the algorithm has the potential as an alternative paradigm for visualizing large-scale networks. Further studies in this direction are recommended.
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Citation:
Chaomei Chen, Natasha Lobo,
"Semantically Modified Diffusion Limited Aggregation for Visualizing Large-Scale Networks,"
iv,
p. 576,
Seventh International Conference on Information Visualization (IV'03),
2003
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