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 ...

Graph theory isn’t enough. The mathematical language for talking about connections, which usually depends on networks — vertices (dots) and edges (lines connecting them) — has been an invaluable way ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...

Neo4j, a provider of graph technology, is launching Neo4j for Graph Data Science, a data science environment built to harness the predictive power of relationships for enterprise deployments. Neo4j ...

The design, implementation, and analysis of abstract data types, data structures and their algorithms. Topics include: data and procedural abstraction, amortized data structures, trees and search ...

Graph databases are the fastest growing category in all of data management, according to DB-Engines.com, a database consultancy. Since seeing early adoption by companies including Twitter, Facebook ...

Machine learning, task automation and robotics are already widely used in business. These and other AI technologies are about to multiply, and we look at how organizations can best take advantage of ...