Large graphs containing hundreds of thousands of nodes and millions of edges pose challenges for pattern finding, outlier detection, and community detection tasks. GMine proposes an innovative framework using a hierarchical graph partitioning representation called SuperGraph and Graph-Tree along with a graph summarization technique called CEPS. This allows graphs to be interactively explored globally and locally in a visual environment, addressing issues of excessive processing requirements and cluttered images from drawing large graphs.