We survey foundational features underlying modern graph query languages. We first
discuss two popular graph data models: edge-labelled graphs, where nodes are connected …

Recent demands for storing and querying big data have revealed various shortcomings of
traditional relational database systems. This, in turn, has led to the emergence of a new kind …

Cyber threat intelligence (CTI) is being used to search for indicators of attacks that might
have compromised an enterprise network for a long time without being discovered. To have …

Simple graph algorithms such as PageRank have been the target of numerous hardware
accelerators. Yet, there also exist much more complex graph mining algorithms for problems …

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 …

The dramatic proliferation of sophisticated networks has resulted in a growing need for
supporting effective querying and mining methods over such large-scale graph-structured …

Space-time processing can improve network capacity, coverage, and quality by reducing co-
channel interference (CCI) while enhancing diversity and array gain. This article focuses …

Graph pattern matching is typically defined in terms of subgraph isomorphism, which makes
it an np-complete problem. Moreover, it requires bijective functions, which are often too …

Background Graphs can represent biological networks at the molecular, protein, or species
level. An important query is to find all matches of a pattern graph to a target graph …

Graph pattern matching is commonly used in a variety of emerging applications such as
social network analysis. These applications highlight the need for studying the following two …