As many readers may know, graph theory is a fundamental branch of mathematics that
examines networks consisting of nodes and edges, with a focus on their paths, structures …

Graph theory has been widely studied, resulting in numerous applications across various
felds. Among its many topics, Automata and Graph Grammar have emerged as signifcant …

Treewidth is a parameter that measures how tree-like a relational instance is, and whether it
can reasonably be decomposed into a tree. Many computation tasks are known to be …

We review the basics of data provenance in relational databases. We describe different
provenance formalisms, from Boolean provenance to provenance semirings and beyond …

An uncertain graph (also known as probabilistic graph) is a generic model to represent
many real-world networks from social to biological. In recent times, analysis and mining of …

Large-scale, highly interconnected networks, which are often modeled as graphs, pervade
both our society and the natural world around us. Uncertainty, on the other hand, is inherent …

Uncertain, or probabilistic, graphs have been increasingly used to represent noisy linked
data in many emerging applications, and have recently attracted the attention of the …

Graph is a famous data structure that has prevalent applications in the real world, including
social networks, biological networks, and computer networks. In these applications, graph …

Community search (CS) on graphs returns the largest densely connected vertex subset
containing a query vertex, namely k-community, where every vertex's degree in the induced …

We propose Sage, a system for uncertain network analysis. Algorithms for uncertain network
analysis require large amounts of memory and computing resources as they sample a large …