Subgraph counting is a fundamental graph analysis task which has been widely used in
many applications. As the problem of subgraph counting is NP-complete and hence …

Graphs are valuable data structures used to represent complex relationships between
entities in a wide range of applications, such as social networks and chemical reactions …

The team discovery task is concerned with finding a group of experts from a collaboration
network who would collectively cover a desirable set of skills. Most prior work for team …

A variety of complex systems, including social and communication networks, financial
markets, biology, and neuroscience are modeled using temporal graphs that contain a set of …

Frequent pattern mining (FPM) on large graphs has received more and more attention due
to its importance in various applications, including social media analysis. The FPM models …

Sampling random nodes is a fundamental algorithmic primitive in the analysis of massive
networks, with many modern graph mining algorithms critically relying on it. We consider the …

Subgraph Pattern Mining (SPM) is an important class of graph applications that aim to
discover structural patterns in a graph. Due to the enormous exploration space, SPM is in …

With the rapid growth of big data analysis, graphs have become an important data structure
in relationship extraction and learning. However, the complexity of graph structure increases …

Simplicial complexes are a generalization of graphs that model higher-order relations. In this
paper, we introduce simplicial patterns—that we call simplets—and generalize the task of …

Frequent itemset mining (FIM) is a major component in association rule mining, significantly
influencing its performance. FIM is a computationally intensive nondeterministic polynomial …