GMine: a system for scalable, interactive graph visualization and mining

  • Authors:
  • José F. Rodrigues, Jr.;Hanghang Tong;Agma J. M. Traina;Christos Faloutsos;Jure Leskovec

  • Affiliations:
  • Dept. de Computação, Inst. de Ciências Matemáticas e de Computação, Universidade de São Paulo, São Carlos, SP, Brazil;Carnegie Mellon University, Pittsburgh, Pennsylvania;Dept. de Computação, Inst. de Ciências Matemáticas e de Computação, Universidade de São Paulo, São Carlos, SP, Brazil;Carnegie Mellon University, Pittsburgh, Pennsylvania;Carnegie Mellon University, Pittsburgh, Pennsylvania

  • Venue:
  • VLDB '06 Proceedings of the 32nd international conference on Very large data bases
  • Year:
  • 2006

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Abstract

Several graph visualization tools exist. However, they are not able to handle large graphs, and/or they do not allow interaction. We are interested on large graphs, with hundreds of thousands of nodes. Such graphs bring two challenges: the first one is that any straightforward interactive manipulation will be prohibitively slow. The second one is sensory overload: even if we could plot and replot the graph quickly, the user would be overwhelmed with the vast volume of information because the screen would be too cluttered as nodes and edges overlap each other.Our GMine system addresses both these issues, by using summarization and multi-resolution. GMine offers multi-resolution graph exploration by partitioning a given graph into a hierarchy of communities-within-communities and storing it into a novel R-treelike structure which we name G-Tree. GMine offers summarization by implementing an innovative subgraph extraction algorithm and then visualizing its output.