These algorithms simultaneously learn a graph structure and the edge strength of the connected nodes.

Correlations between the degrees of connected nodes develop spontaneously in the BA model because of the way the network evolves.

An example of a heuristic for a node would be a summation of how many unvisited nodes are "close by" a connected node.

Spreading activation refers to the firing of connected nodes in associated memory links.

The transform can be extended to greater numbers of connected nodes and is then known as the star-mesh transform.

The mass-spring model is converted into a system of constraints, which demands that the distance between the connected nodes be equal to the initial distance.

Once a bridge learns the addresses of its connected nodes, it forwards data link layer frames using a layer 2 forwarding method.

In a peer-to-peer network, tasks are distributed across all connected nodes.

Where cycles have been broken, numeric suffix labels are included to indicate the connected nodes.

The node at the head of the queue is subsequently expanded, adding the next set of connected nodes with the total path cost from the root to the respective node.