connectionsgenerates
connectionsgenerates is a term used in data science and network theory to describe a class of generative processes that output connection structures, such as graphs or networks, among a set of entities. The central aim is to produce plausible links between nodes based on observed data and contextual signals, enabling the construction or augmentation of knowledge graphs, social graphs, or biological networks.
Methods encompassed by connectionsgenerates include probabilistic graph models, such as stochastic block models and edge-existence priors,
Common applications include predicting missing links in social networks, inferring protein–protein interactions, recommending items through co-purchase
Evaluation typically considers accuracy of predicted links, graph-level properties such as degree distribution and clustering, and
See also: graph generation, link prediction, graph neural networks, generative models, network science.