Demonstrating interactive multi-resolution large graph exploration

Zhiyuan Lin, Nan Cao, Hanghang Tong, Fei Wang, U. Kang, Duen Horng Polo Chau

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

9 Scopus citations

Abstract

We present a scalable, interactive graph visualization system to support multi-resolution exploration of million-node graphs in real time. By adapting a state-of-the-art graph algorithm, called Slash & Burn, our prototype system generates a multi-resolution view of graphs with up to 69 million edges under a few seconds. We are experimenting with interaction techniques that help users interactively explore this overview and drill down into details. While many visualization systems for million-node graphs require dedicated servers to process the graphs, our prototype runs on a commodity laptop computer. We aim to handle graphs that are at least an order of magnitude (100M edges) larger than what current systems can support. We demonstrate our system's usage, benefits, and scalability using two large graphs: a Live Journal friendship network with 69 million edges, and a related-movies network from Rotten Tomatoes with 200K edges.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE 13th International Conference on Data Mining Workshops, ICDMW 2013
PublisherIEEE Computer Society
Pages1097-1100
Number of pages4
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event2013 13th IEEE International Conference on Data Mining Workshops, ICDMW 2013 - Dallas, TX, United States
Duration: Dec 7 2013Dec 10 2013

Other

Other2013 13th IEEE International Conference on Data Mining Workshops, ICDMW 2013
CountryUnited States
CityDallas, TX
Period12/7/1312/10/13

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Keywords

  • Graph decomposition
  • Hubs and spokes
  • Interactive graph visualization
  • Multi-resolution

ASJC Scopus subject areas

  • Software

Cite this

Lin, Z., Cao, N., Tong, H., Wang, F., Kang, U., & Chau, D. H. P. (2013). Demonstrating interactive multi-resolution large graph exploration. In Proceedings - IEEE 13th International Conference on Data Mining Workshops, ICDMW 2013 (pp. 1097-1100). [6754046] IEEE Computer Society. https://doi.org/10.1109/ICDMW.2013.124