Scalable Temporal Latent Space Inference for Link Prediction in Dynamic Social Networks. Zhu, L., Guo, D., Yin, J., Steeg, G. V., & Galstyan, A. *IEEE Transactions on Knowledge and Data Engineering*, 28(10):2765–2777, October, 2016. doi bibtex @article{zhu_scalable_2016,
title = {Scalable {Temporal} {Latent} {Space} {Inference} for {Link} {Prediction} in {Dynamic} {Social} {Networks}},
volume = {28},
issn = {1041-4347},
doi = {10.1109/TKDE.2016.2591009},
number = {10},
journal = {IEEE Transactions on Knowledge and Data Engineering},
author = {Zhu, L. and Guo, D. and Yin, J. and Steeg, G. V. and Galstyan, A.},
month = oct,
year = {2016},
keywords = {Computational efficiency, Computational modeling, Electronic mail, Heuristic algorithms, Latent space model, Prediction algorithms, Predictive models, Social network services, dynamic social networks, global optimization algorithm, graph snapshots, graph theory, incremental updates, inference mechanisms, link prediction, local updates, network structure, network theory (graphs), non-negative matrix factorization, optimisation, predictive power factor, real-world dynamic networks, scalability factor, scalable temporal latent space inference, set theory, social network analysis, social sciences computing, temporal link prediction, unobserved latent space representation},
pages = {2765--2777},
}

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