Shafali Gupta, Ulka Panchal
Abstract: Thousands of existing applications nodes and edges on the order of hundreds of millions of graphically produced. To take Benefits such as illustrations; patterns; outliers and communities should be able to find these functions are performed in a Interactive environment where human expertise can guide procedure. larger graphs; however; there are some challenges: Highly prohibitive processing requirements; and drawing a hundred-thousand nodes results in cluttered images difficult to Understand these problems; we would like an innovative structure trees suited to any kind of Visual design graph. GMine integrates 1) underlines a representation organized hierarchies Super Graph of Division and conceptual graph-tree; And 2) a graph representation summarization method tracing our CEPS deals with connection problem Sub linear complexity; with a graph to a single node or nodes of a hierarchy; a neighborhood group to allow for an understanding of the aspects A proof of concept with one click.; a system in which large graphs can be GMine the Visual environment is instantiated Globally and locally. The graph mining method is based on the clustering; decision tree approaches; classifications; which are fundamentals of data mining. The visualization of graphs is depends on efficient method graph mining only; therefore in paper we have discussed more on graph mining methods and work on large graph representation using the efficient method and frameworks.
Keywords: Graph analysis system, graph representation, data structures, graph mining, graph visualization