Journal
ISCIENCE
Volume 24, Issue 11, Pages -Publisher
CELL PRESS
DOI: 10.1016/j.isci.2021.103217
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Funding
- National Natural Science Foundation of China [11975071, 61673086]
- Science Strength Promotion Programmer of University of Electronic Science and Technology of China [Y03111023901014006]
- Fundamental Research Funds for the Central Universities of China [ZYGX2016J196]
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This review discusses the significance of link prediction in network science, summarizes various approaches and evaluation metrics, and highlights the challenges for future research in this field.
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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