Many business cases exploiting big data have been realised in recent years; Twitter,
LinkedIn, and Facebook are examples of companies in the social networking domain. Other …

Knowledge is indispensable to understanding. The ongoing information explosion highlights
the need to enable machines to better understand electronic text in human language. Much …

The ability to handle large scale graph data is crucial to an increasing number of
applications. Much work has been dedicated to supporting basic graph operations such as …

Much work has been devoted to supporting RDF data. But state-of-the-art systems and
methods still cannot handle web scale RDF data effectively. Furthermore, many useful and …

Temporal property graphs are graphs whose structure and properties change over time.
Temporal graph datasets tend to be large due to stored historical information, asking for …

Dependency analysis of critical infrastructures is a computationally intensive problem when
dealing with large-scale, cross-sectoral, cascading and common-cause failures. The …

Dependency risk graphs have been proposed as a tool for analyzing cascading failures due
to critical infrastructure dependency chains. However, dependency chain analysis is not by …

Threat models and attack graphs have been used more than 20 years by enterprises and
organizations for mapping the actions of potential adversaries, analyzing the effects of …

Graph partitioning is a key issue in graph database processing systems for achieving high
efficiency on Cloud. However, the balanced graph partitioning itself is difficult because it is …

We present a parallel k-clique listing algorithm with improved work bounds (for the same
depth) in sparse graphs with low degeneracy or arboricity. We achieve this by introducing …