链接预测的进展与挑战
Progresses and Challenges in Link Prediction
摘要：
链路预测是网络科学中的一个典型问题，其目的是在已知网络拓扑的基础上估计未观测到的链路的存在概率。在简要介绍了链接预测的标准问题和度量方法之后，本文将从近十年来的大量相关文献中，归纳总结局部相似性指标、链接可预测性、网络嵌入、矩阵补全、集成学习等方面的代表性研究进展。最后，本观点将概述一些长期存在的挑战，为未来的研究。
英文摘要：
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 metrics of link prediction, this Perspective will summarize representative progresses about local similarity indices, link predictability, network embedding, matrix completion, ensemble learning and others, mainly extracted from thousands of related publications in the last decade. Finally, this Perspective will outline some long-standing challenges for future studies.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
