Graph algorithms constitute a fundamental area of computational research that focuses on the analysis and manipulation of graph structures, which represent systems of interconnected entities. In ...

Graph labeling is a central topic in combinatorial optimisation that involves assigning numerical or categorical labels to vertices or edges of a graph subject to specific constraints. This framework ...

In algorithms, as in life, negativity can be a drag. Consider the problem of finding the shortest path between two points on a graph — a network of nodes connected by links, or edges. Often, these ...

Graphs are widely used to represent complex relationships in everyday applications such as social networks, bioinformatics, ...

Neo4j is both the original graph database and the continued leader in the graph database market. Designed to store entities and relationships, and optimized to perform graph operations such as ...

Graph databases explicitly express the connections between nodes, and are more efficient at the analysis of networks (computer, human, geographic, or otherwise) than relational databases. There has ...

Graphs are widely used to represent complex relationships in everyday applications such as social networks, bioinformatics, and recommendation ...

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 ...