Recently, the topic of community search (CS) has gained plenty of attention. Given a query
vertex, CS looks for a dense subgraph that contains it. Existing studies mainly focus on …

We propose high-order hypergraph walks as a framework to generalize graph-based
network science techniques to hypergraphs. Edge incidence in hypergraphs is quantitative …

Bipartite graphs are widely used to model relation-ships between two types of entities.
Community search retrieves densely connected subgraphs containing a query vertex, which …

Densest subgraph discovery (DSD) is a fundamental problem in graph mining. It has been
studied for decades, and is widely used in various areas, including network science …

Cohesive subgraph mining in bipartite graphs becomes a popular research topic recently.
An important structure k-bitruss is the maximal cohesive subgraph where each edge is …

Maximal bicliques are effective to reveal meaningful information hidden in bipartite graphs.
Maximal biclique enumeration (MBE) is challenging since the number of the maximal …

The studies of k-truss based community search demonstrated that it can find high-quality
personalized com-munities with good properties such as high connectivity and bounded …

Recently there emerge many distributed algorithms that aim at solving subgraph matching at
scale. Existing algorithm-level comparisons failed to provide a systematic view of distributed …

Subgraph enumeration is a fundamental problem in graph analytics, which aims to find all
instances of a given query graph on a large data graph. In this paper, we propose a system …

With the advent of a wide spectrum of recent applications, querying heterogeneous
information networks (HINs) has received a great deal of attention from both academic and …