挖掘图核的简单线性算法

摘要：

Batagelj和Zaversnik提出了一个线性算法的著名的$k$ -核心分解问题。然而，当$k$ -核心所需的一个给定的$k$，我们发现，一个简单的线性算法，不需要排序工程挖掘$k$ -核心。此外，该算法还可以扩展到在线性时间内从$p$ -partite图中挖掘$(k_1, k_2,\ldots, k_p)$ -core，并且该挖掘方法可以在分布式计算环境中有效地实现，与最著名的分布式$k$ -core分解方法相比具有更低的消息复杂度。

英文摘要：

Batagelj and Zaversnik proposed a linear algorithm for the well-known $k$-core decomposition problem. However, when $k$-cores are desired for a given $k$, we find that a simple linear algorithm requiring no sorting works for mining $k$-cores. In addition, this algorithm can be extended to mine $(k_1, k_2,\ldots, k_p)$-cores from $p$-partite graphs in linear time, and this mining approach can be efficiently implemented in a distributed computing environment with a lower message complexity bound in comparison with the best known method of distributed $k$-core decomposition.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。