On Efficient Large Maximal Biplex Discovery (Extended abstract)

Cohesive subgraph discovery is an important problem in bipartite graph mining. In this paper, we focus on one kind of cohesive structure, called
$k$
-biplex, where each vertex of one side is disconnected from at most
$k$
vertices of the other side. We consider the large maximal
$k$
-biplex enumeration problem which is to list all those maximal
$k$
-biplexes with the number of vertices at each side at least a non-negative integer
$\theta$
. This formulation aims to find non-redundant results by excluding non-maximal ones and has various applications. Existing approaches suffer from massive redundant computations and can only run on small and moderate datasets. Towards improving scalability, we propose an efficient tree-based algorithm with two advanced strategies and powerful pruning techniques. Experimental results show the superiority of our algorithm over existing approaches.