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Butterfly Counting on Uncertain Bipartite Networks

Alexander Zhou, Yue Wang, Lei Chen

2022Year
25Citations
2Top-tier citations

Abstract

When considering uncertain bipartite networks, the number of instances of the popular graphlet structure the butterfly may be used as an important metric to quickly gauge information about the network. This Uncertain Butterfly Count has practical usages in a variety of areas such as biomedical/biological fields, E-Commerce and road networks. In this paper we formally define the uncertain butterfly structure (in which the existential probability of the butterfly is greater than or equal to some user-defined threshold t ) as well as the Uncertain Butterfly Counting Problem (to determine the number of unique instances of this structure on any uncertain bipartite network). We then examine exact solutions by proposing a non-trivial baseline (UBFC) as well as an improved solution (IUBFC) which reduces the time complexity and employs heuristics to further reduce the runtime in practice. In addition to exact solutions, we propose two approximate solutions via sampling, UBS and PES , which can be used to quickly estimate the Uncertain Butterfly Count, a powerful tool when the exact count is unnecessary. Using a range of networks with different edge existential probability distributions, we validate the efficiency and effectiveness of our solutions.

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