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ECWAY TECHNOLOGIES
IEEE PROJECTS & SOFTWARE DEVELOPMENTS
OUR OFFICES @ CHENNAI / TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE
CELL: +91 98949 17187, +91 875487 2111 / 3111 / 4111 / 5111 / 6111
VISIT: www.ecwayprojects.com MAIL TO: ecwaytechnologies@gmail.com

LARGE GRAPH ANALYSIS IN THE GMINE SYSTEM
ABSTRACT:

Current applications have produced graphs on the order of hundreds of thousands of nodes and
millions of edges. To take advantage of such graphs, one must be able to find patterns, outliers,
and communities. These tasks are better performed in an interactive environment, where human
expertise can guide the process. For large graphs, though, there are some challenges: the
excessive processing requirements are prohibitive, and drawing hundred-thousand nodes results
in cluttered images hard to comprehend.

We propose an innovative framework suited for any kind of tree-like graph visual design. GMine
integrates 1) a representation for graphs organized as hierarchies of partitions—the concepts of
SuperGraph and Graph-Tree; and 2) a graph summarization methodology—CEPS. Our graph
representation deals with the problem of tracing the connection aspects of a graph hierarchy with
sub linear complexity, allowing one to grasp the neighborhood of a single node or of a group of
nodes in a single click. As a proof of concept, the visual environment of GMine is instantiated as
a system in which large graphs can be investigated globally and locally.

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Dotnet large graph analysis in the g mine system

  • 1. ECWAY TECHNOLOGIES IEEE PROJECTS & SOFTWARE DEVELOPMENTS OUR OFFICES @ CHENNAI / TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE CELL: +91 98949 17187, +91 875487 2111 / 3111 / 4111 / 5111 / 6111 VISIT: www.ecwayprojects.com MAIL TO: ecwaytechnologies@gmail.com LARGE GRAPH ANALYSIS IN THE GMINE SYSTEM ABSTRACT: Current applications have produced graphs on the order of hundreds of thousands of nodes and millions of edges. To take advantage of such graphs, one must be able to find patterns, outliers, and communities. These tasks are better performed in an interactive environment, where human expertise can guide the process. For large graphs, though, there are some challenges: the excessive processing requirements are prohibitive, and drawing hundred-thousand nodes results in cluttered images hard to comprehend. We propose an innovative framework suited for any kind of tree-like graph visual design. GMine integrates 1) a representation for graphs organized as hierarchies of partitions—the concepts of SuperGraph and Graph-Tree; and 2) a graph summarization methodology—CEPS. Our graph representation deals with the problem of tracing the connection aspects of a graph hierarchy with sub linear complexity, allowing one to grasp the neighborhood of a single node or of a group of nodes in a single click. As a proof of concept, the visual environment of GMine is instantiated as a system in which large graphs can be investigated globally and locally.