Link Prediction

Link prediction is a task in network analysis that aims to predict the likelihood of a connection between two nodes in a graph or network. It is commonly used in social network analysis, recommender systems, and other applications where connections between entities are of interest.

Link prediction algorithms typically calculate similarity scores between node pairs based on various network features, such as the number of common neighbors, the Jaccard coefficient, or other graph-based metrics. Higher similarity scores indicate a higher likelihood of a connection between the nodes. Machine learning models can also be trained to predict links based on node features and network structure.

To learn more about link prediction and its applications, you can explore the following resources: