arXiv:1010.0725physics.soc-ph
Link Prediction in Complex Networks: A Survey
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Abstract
Link prediction in complex networks has attracted increasing attention from both physical and computer science communities. The algorithms can be used to extract missing information, identify spurious interactions, evaluate network evolving mechanisms, and so on. This article summaries recent progress about link prediction algorithms, emphasizing on the contributions from physical perspectives and approaches, such as the random-walk-based methods and the maximum likelihood methods. We also introduce three typical applications: reconstruction of networks, evaluation of network evolving mechanism and classification of partially labelled networks. Finally, we introduce some applications and outline future challenges of link prediction algorithms.
The last sentence of your post is known as 'link-prediction' in the networks literature. [1] is a pretty comprehensive survey from the networks perspective. In many cases this reduces to learning pairwise distances between vertices. The network translation view is interesting…
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