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

Graphs are among the most widely-used data structures in machine learning. Their power comes from the flexibility of capturing relations (edges) of collections of entities (nodes) which arise in a ...

Knowledge graphs represent a leap in how AI systems comprehend and structure information. Imagine a vast web where each point, or ‘node,’ symbolizes an entity – be it a person, place, or ...

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

Knowledge graphs , which are essential for internet searches and machine learning, use a graph structure to link various pieces of knowledge and link data to perform knowledge exploration and ...

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.