This paper proposed a new algorithm, which was based on K2 tree, one of data structures to describe large graph, to achieve better compression ratio. In this proposed algorithm, used the depth-first search with heuristic rule to reorder all the vertices in the network data, and in order to take full advantage of community structure in the network data and decrease stor-age cost, advanced a self-adapt way to determine the best value for variable K. Finally, presented a detail optimizing algorithm description based on K2 tree. A series of experimental results on real and simulated networks prove the effectiveness of the new algorithm.%针对大图数据的一种表达方法——K2树,提出了相应的压缩优化算法.该算法利用带有启发式规则的DFS编码对图中所有节点进行重新编码,并通过自适应调整参数K,使得K2树能够充分利用网络中的社团结构特性,从而降低空间代价.给出了K2树的优化算法描述,并针对一系列真实网络和模拟网络进行了实验,验证了优化算法具有较好的压缩效果.
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