Networks are a general language for describing complex systems of interacting entities. In the real world, a network always contains massive nodes, edges and additional complex information which leads to high complexity in computing and analyzing tasks. Network embedding aims at transforming one network into a low dimensional vector space which benefits the downstream network analysis tasks. In this survey, we provide a systematic overview of network embedding techniques in addressing challenges appearing in networks. We first introduce concepts and challenges in network embedding. Afterwards, we categorize network embedding methods using three categories, including static homogeneous network embedding methods, static heterogeneous network embedding methods and dynamic network embedding methods. Next, we summarize the datasets and evaluation tasks commonly used in network embedding. Finally, we discuss several future directions in this field.

网络是描述交互实体的复杂系统的通用语言。在现实世界中，网络始终包含大量节点，边缘和其他复杂信息，从而导致计算和分析任务的复杂性很高。网络嵌入旨在将一个网络转换为低维向量空间，从而有利于下游网络分析任务。在本次调查中，我们提供了网络嵌入技术的系统概述，以应对网络中出现的挑战。我们首先介绍网络嵌入的概念和挑战。然后，我们将网络嵌入方法分为三类，包括静态同构网络嵌入方法，静态异构网络嵌入方法和动态网络嵌入方法。下一个，我们总结了网络嵌入中常用的数据集和评估任务。最后，我们讨论了该领域的未来发展方向。