链接预测研究进展综述

Jiahao Li, Linlan Liu, Jian Shu
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引用次数: 0

摘要

链路预测是一种基于当前动态网络信息预测实体之间未来新增或缺失关系的技术。在简要介绍了链接预测的标准问题和评价指标之后,本文将总结矩阵分解、概率模型、网络嵌入、深度学习等方面的代表性进展,主要摘自近十年来的相关出版物。最后,本文概述了未来研究的一些长期挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Progresses in Link Prediction: A Survey
Link prediction is a technique to forecast future new or missing relationships between entities based on the current dynamic network information. After a brief introduction of the standard problem and evaluation metrics of link prediction, this review will summarize representative progresses about matrix factorization, probabilistic models, network embedding, deep 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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