We propose data-driven one-pass streaming algorithms for estimating the number of
triangles and four cycles, two fundamental problems in graph analytics that are widely …

Given a stream of edge additions and deletions, how can we estimate the count of triangles
in it? If we can store only a subset of the edges, how can we obtain unbiased estimates with …

We consider space-efficient single-pass estimation of the number of butterflies, a
fundamental bipartite graph motif, from a massive bipartite graph stream where each edge …

We study the fundamental problem of butterfly (ie,(2, 2)-bicliques) counting in bipartite
streaming graphs. Similar to triangles in unipartite graphs, enumerating butterflies is crucial …

If we cannot store all edges in a dynamic graph, which edges should we store to estimate
the triangle count accurately? Counting triangles (ie, cliques of size three) is a fundamental …

Triangle approximate counting has emerged as a prominent issue in graph stream research
in the past few years, with applications ranging from social network analysis to web topic …

As the popularity of graph data increases, there is a growing need to count the occurrences
of subgraph patterns of interest, for a variety of applications. Many graphs are massive in …

A bipartite graph extensively models relationships between real-world entities of two
different types, such as user-product data in e-commerce. Such graph data are inherently …

In this work, we present the first efficient and practical algorithm for estimating the number of
triangles in a graph stream using predictions. Our algorithm combines waiting room …

A great variety of complex systems, from user interactions in communication networks to
transactions in financial markets, can be modeled as temporal graphs consisting of a set of …