Dynamic graph algorithms and data structures represent a vital research frontier in computer science, underpinning applications from network analysis to real-time system monitoring.

Graph-structured data are pervasive in the real-world such as social networks, molecular graphs and transaction networks.

Graphs naturally generalize unstructured vectorial data and structured data such as time series, images or bags of entities. The goal of this course is to provide an overview of the fundamental ...

The four pillars of graph adoption This confluence of graph analytics, graph databases, graph data science, machine learning, and knowledge graphs is what makes graph a foundational technology.

József Balogh, Robert Morris, Wojciech Samotij, Lutz Warnke, The typical structure of sparse Kr+1-free graphs, Transactions of the American Mathematical Society, Vol. 368, No. 9 (September 2016), pp.

Data-hungry AI applications are fed complex information, and that's where graph databases and knowledge graphs play a crucial role.

Informatica's Gaurav Pathak and Fivetran's George Fraser discussed the evolving data stack and the role of metadata knowledge graphs during Supercloud 7.

Direct Acyclic Graph or DAG may be it. What is DAG? DAG is a directed graph data structure that uses a topological ordering. The sequence can only go from earlier to later.

Knowledge graphs are a valuable tool that organizations can use to manage the vast amounts of data they collect, store, and analyze. At Data Summit 2023, Joseph Hilger, COO, Enterprise Knowledge LLC ...