大型网络：一项调查
Big Networks: A Survey
摘要：
网络是用顶点和链接来表示复杂系统的典型表达形式，其中网络组件之间的交互模式是错综复杂的。网络可以是不随时间变化的静态网络，也可以是随时间演变的动态网络。在网络规模爆炸式增长的新形势下，网络分析的复杂性也随之发生了变化。本文介绍了一个新的网络科学概念--大网络。大网络一般规模较大，内部结构复杂，层次较高。本文提出了一个指导性框架，从大网络的角度深入了解网络科学领域的主要主题。本文首先从微观、中观和宏观三个层次介绍了大网络的结构特征。然后，我们讨论大型网络分析的一些最先进的高级主题。系统地介绍了大网络模型及其相关方法，包括排序方法、划分方法和网络嵌入算法。然后回顾了大网络中的一些典型应用，如社区发现、链接预测、推荐等，并指出了一些需要进一步研究的关键问题。
英文摘要：
A network is a typical expressive form of representing complex systems in terms of vertices and links, in which the pattern of interactions amongst components of the network is intricate. The network can be static that does not change over time or dynamic that evolves through time. The complication of network analysis is different under the new circumstance of network size explosive increasing. In this paper, we introduce a new network science concept called big network. Big networks are generally in large-scale with a complicated and higher-order inner structure. This paper proposes a guideline framework that gives an insight into the major topics in the area of network science from the viewpoint of a big network. We first introduce the structural characteristics of big networks from three levels, which are micro-level, meso-level, and macro-level. We then discuss some state-of-the-art advanced topics of big network analysis. Big network models and related approaches, including ranking methods, partition approaches, as well as network embedding algorithms are systematically introduced. Some typical applications in big networks are then reviewed, such as community detection, link prediction, recommendation, etc. Moreover, we also pinpoint some critical open issues that need to be investigated further.
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。
