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具有改进最坏情况时间复杂度保证的最大双 клиques 枚举:一种分区策略

Maximal Biclique Enumeration with Improved Worst-Case Time Complexity Guarantee: A Partition-Oriented Strategy

College of Computer Science, Beijing University of Technology(北京工业大学计算机学院);State Key Laboratory of Novel Software Technology, Nanjing University(南京大学软件新技术国家重点实验室);College of Computing and Data Science, Nanyang Technological University(南洋理工大学计算与数据科学学院)

Kaixin Wang, Kaiqiang Yu, Cheng Long

AI总结:

本文提出IPS算法,通过改进的终止条件和枢轴选择策略,将最大双 клиques 枚举的最坏情况时间复杂度降低至O(m·α^n + n·β),优于现有方法。

摘要:

在双图中最大双 клиques 枚举问题是一个基础性问题,具有在电子商务和交易网络中的广泛应用。大多数现有研究采用分支限界框架,该框架递归地扩展一个部分双 клиques,直到无法再添加更多顶点为止。配备基本的枢轴选择策略,所有最先进的方法的最坏情况时间复杂度都不优于O(m·(√2)^n),其中m和n分别是图中的边数和顶点数。在本文中,我们介绍了一种新的分支限界(BB)算法IPS。在IPS中,我们放松了现有方法的严格终止准则,允许在当前分支中所有最大双 клиques 可以在与内部最大双 клиques 数量成比例的时间内输出时终止,从而减少所需的分支总数。第二,为了充分利用新的终止条件,我们提出了一种改进的枢轴选择策略,该策略与新的终止条件很好地匹配,以实现更好的理论和实际性能。形式上,IPS将最坏情况时间复杂度改进为O(m·α^n + n·β),其中α(≈1.3954)是x^4-2x-1=0方程的最大正根,β代表图中的最大双 клиques 数量。这一结果超越了所有现有算法,因为α严格小于√2,且β理论上最多为(√2)^n-2。此外,我们应用了一个基于包含-排除的框架来提升IPS的性能,将最坏情况时间复杂度改进为O(n·γ²·α^γ + γ·β),适用于大规模稀疏图(γ是一个满足γ<<n的参数)。

英文摘要:

The maximal biclique enumeration problem in bipartite graphs is fundamental and has numerous applications in E-commerce and transaction networks. Most existing studies adopt a branch-and-bound framework, which recursively expands a partial biclique with a vertex until no further vertices can be added. Equipped with a basic pivot selection strategy, all state-of-the-art methods have a worst-case time complexity no better than $O(m\cdot (\sqrt{2})^n)$}, where $m$ and $n$ are the number of edges and vertices in the graph, respectively. In this paper, we introduce a new branch-and-bound (BB) algorithm \texttt{IPS}. In \texttt{IPS}, we relax the strict stopping criterion of existing methods by allowing termination when all maximal bicliques within the current branch can be outputted in the time proportional to the number of maximal bicliques inside, reducing the total number of branches required. Second, to fully unleash the power of the new termination condition, we propose an improved pivot selection strategy, which well aligns with the new termination condition to achieve better theoretical and practical performance. Formally, \texttt{IPS} improves the worst-case time complexity to $O(m\cdot α^n + n\cdot β)$, where $α(\approx 1.3954)$ is the largest positive root of $x^4-2x-1=0$ and $β$ represents the number of maximal bicliques in the graph, respectively. This result surpasses that of all existing algorithms given that $α$ is strictly smaller than $\sqrt{2}$ and $β$ is at most $(\sqrt{2})^n-2$ theoretically. Furthermore, we apply an inclusion-exclusion-based framework to boost the performance of \texttt{IPS}, improving the worst-case time complexity to $O(n\cdot γ^2\cdotα^γ+ γ\cdot β)$ for large sparse graphs ($γ$ is a parameter satisfying $γ\ll n$ for sparse graphs).

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。

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