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The application of appropriate graph data compression technology to store and manipulate graph data with tens of thousands of nodes and edges is a prerequisite for analyzing large-scale graph data. The traditional K2-tree representation scheme mechanically partitions the adjacency matrix, which causes the dense interval to be split, resulting in additional storage overhead. As the size of the graph data increases, the query time of K2-tree continues to increase. In view of the above problems,doi:10.1155/2020/2354875 fatcat:2o33w42i5rbezpxfnynhwj6zwm