With the rapid development of information technologies, various big graphs are prevalent in
many real applications (eg, social media and knowledge bases). An important component of …

As a powerful expression of human knowledge in a structural form, knowledge graph (KG)
has drawn great attention from both the academia and the industry and a large number of …

Given a graph G and a vertex q∈ G, the community search query returns a subgraph of G
that contains vertices related to q. Communities, which are prevalent in attributed graphs …

Querying heterogeneous and large-scale knowledge graphs is expensive. This paper
studies a graph summarization framework to facilitate knowledge graph search.(1) We …

Nowadays graphical datasets are having a vast amount of applications. As a result, graph
mining—mining graph datasets to extract frequent subgraphs—has proven to be crucial in …

We propose a class of functional dependencies for graphs, referred to as GFDs. GFDs
capture both attribute-value dependencies and topological structures of entities, and …

This article presents GRAPE, a parallel GRAP h E ngine for graph computations. GRAPE
differs from prior systems in its ability to parallelize existing sequential graph algorithms as a …

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 …

This article studies discovery of Graph Functional Dependencies (GFDs), a class of
functional dependencies defined on graphs. We investigate the fixed-parameter tractability …

This paper tackles two challenges to discovery of graph rules. Existing discovery methods
often (a) return an excessive number of rules, and (b) do not scale with large graphs given …