Progresses and challenges in link prediction
Summary: Link prediction is a paradigmatic problem in network science, which aims at estimating the existence likelihoods of nonobserved links, based on known topology. After a brief introduction of the standard problem and evaluation metrics of link prediction, this review will summarize representa...
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2021
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oai:doaj.org-article:32c023c3d57e4e41abc8bcbdac6f6ada2021-11-20T05:08:22ZProgresses and challenges in link prediction2589-004210.1016/j.isci.2021.103217https://doaj.org/article/32c023c3d57e4e41abc8bcbdac6f6ada2021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2589004221011858https://doaj.org/toc/2589-0042Summary: Link prediction is a paradigmatic problem in network science, which aims at estimating the existence likelihoods of nonobserved links, based on known topology. After a brief introduction of the standard problem and evaluation metrics of link prediction, this review will summarize representative progresses about local similarity indices, link predictability, network embedding, matrix completion, ensemble learning, and some others, mainly extracted from related publications in the last decade. Finally, this review will outline some long-standing challenges for future studies.Tao ZhouElsevierarticleComputer scienceNetworkNetwork topologyScienceQENiScience, Vol 24, Iss 11, Pp 103217- (2021) |
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DOAJ |
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DOAJ |
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EN |
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Computer science Network Network topology Science Q |
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Computer science Network Network topology Science Q Tao Zhou Progresses and challenges in link prediction |
| description |
Summary: Link prediction is a paradigmatic problem in network science, which aims at estimating the existence likelihoods of nonobserved links, based on known topology. After a brief introduction of the standard problem and evaluation metrics of link prediction, this review will summarize representative progresses about local similarity indices, link predictability, network embedding, matrix completion, ensemble learning, and some others, mainly extracted from related publications in the last decade. Finally, this review will outline some long-standing challenges for future studies. |
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article |
| author |
Tao Zhou |
| author_facet |
Tao Zhou |
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Tao Zhou |
| title |
Progresses and challenges in link prediction |
| title_short |
Progresses and challenges in link prediction |
| title_full |
Progresses and challenges in link prediction |
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Progresses and challenges in link prediction |
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Progresses and challenges in link prediction |
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progresses and challenges in link prediction |
| publisher |
Elsevier |
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2021 |
| url |
https://doaj.org/article/32c023c3d57e4e41abc8bcbdac6f6ada |
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AT taozhou progressesandchallengesinlinkprediction |
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