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arXiv · 1906.04548

Spring-Electrical Models For Link Prediction

Yana Kashinskaya·Egor Samosvat·Akmal Artikov
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Abstract

We propose a link prediction algorithm that is based on spring-electrical models. The idea to study these models came from the fact that spring-electrical models have been successfully used for networks visualization. A good network visualization usually implies that nodes similar in terms of network topology, e.g., connected and/or belonging to one cluster, tend to be visualized close to each other. Therefore, we assumed that the Euclidean distance between nodes in the obtained network layout correlates with a probability of a link between them. We evaluate the proposed method against several popular baselines and demonstrate its flexibility by applying it to undirected, directed and bipartite networks.

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Yana Kashinskaya, Egor Samosvat, Akmal Artikov. 2019-05-24. Spring-Electrical Models For Link Prediction. https://arxiv.org/abs/1906.04548

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