LP features
Here, we’ll describe the characteristics that can be attached to a pair of nodes and used as predictors for an LP model. We’ll start with topological features, which are built by analyzing both nodes’ neighborhoods. Then, we explore how to use each node’s features and combine them into a feature vector for the pair.
Topological features
Topological features rely on nodes’ neighborhoods and graph topology to infer new links. We can, for instance, use the following:
- Common neighbors: Given two nodes, A and B, count the number of common neighbors between A and B. This metric assumes that the more common neighbors A and B have, the more likely they are to be connected.
- Adamic-Adar: A variation of the common neighbors approach, the Adamic-Adar metric incorporates the fact that nodes with fewer connections give more information than nodes with many links. In a web page linking hundreds of other pages, the relevance of each...
