- Title
- Big networks : a survey
- Creator
- Bedru, Hayat; Yu, Shuo; Xiao, Xinru; Zhang, Da; Xia, Feng
- Date
- 2020
- Type
- Text; Journal article; Review
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/184665
- Identifier
- vital:16535
- Identifier
-
https://doi.org/10.1016/j.cosrev.2020.100247
- Identifier
- ISBN:1574-0137 (ISSN)
- Abstract
- 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 a big network. A big networks is 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. © 2020 Elsevier Inc.
- Publisher
- Elsevier Ireland Ltd
- Relation
- Computer Science Review Vol. 37, no. (2020), p.
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright © 2020 Elsevier Inc.
- Rights
- Open Access
- Subject
- 46 Information and Computing Sciences; Big networks; Complex networks; Large-scale networks; Network analysis; Network science
- Full Text
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