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

TL;DR

This paper introduces a new branch-and-bound algorithm for maximal biclique enumeration in bipartite graphs, achieving improved worst-case time complexity through a novel termination condition and pivot strategy, with practical enhancements for sparse graphs.

Contribution

The paper proposes the IPS algorithm with a relaxed stopping criterion and an improved pivot strategy, reducing worst-case time complexity and outperforming existing methods.

Findings

Achieves worst-case time complexity of O(m·α^n + n·β) with α≈1.3954

Surpasses all existing algorithms in theoretical worst-case bounds

Incorporates an inclusion-exclusion framework for better performance on sparse graphs

Abstract

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 $O(m\cdot \alpha ^n + n\cdot \beta)$, where $\alpha (\approx 1.3954)$ is the largest positive root of $x^4-2x-1=0$ and $\beta$ represents the number of maximal bicliques in the graph, respectively. This result surpasses that of all existing algorithms given that $\alpha$ is strictly smaller than $\sqrt{2}$ and $\beta$ 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 $O(n\cdot \gamma^2\cdot\alpha^\gamma + \gamma\cdot \beta)$ for large sparse graphs ($\gamma$ is a parameter satisfying $\gamma \ll n$ for sparse graphs).