Modelling relationship between entities in real‐world systems with a simple graph is a
standard approach. However, reality is better embraced as several interdependent …

Graph visualizations encode relationships between objects. Abstracting the objects into
group structures provides an overview of the data. Groups can be disjoint or overlapping …

Graph sampling is frequently used to address scalability issues when analyzing large
graphs. Many algorithms have been proposed to sample graphs, and the performance of …

Finding patterns in graphs has become a vital challenge in many domains from biological
systems, network security, to finance (eg, finding money laundering rings of bankers and …

Attributed subgraph matching is a powerful tool for explorative mining of large attributed
networks. In many applications (eg, network science of teams, intelligence analysis, finance …

Exploring relationships in complex datasets is one of the challenges in today's big data era.
The graph-based visualization approach, which integrates the advantages of graph analysis …

A graph processing system, method and apparatus classifies graphs based on a linearly
computable set of features defined as a feature vector adapted for comparison with the …

When analyzing a visualized network, users need to explore different sections of the network
to gain insight. However, effective exploration of large networks is often a challenge. While …

In this paper, we study the problem of TEAM MEMBER REPLACEMENT--given a team of
people embedded in a social network working on the same task, find a good candidate to …

In this paper, we present a novel visual analytics system called NameClarifier to interactively
disambiguate author names in publications by keeping humans in the loop. Specifically …