- Title
- Motifs in big networks : methods and applications
- Creator
- Yu, Shuo; Xu, Jin; Zhang, Chen; Xia, Feng; Almakhadmeh, Zafer; Tolba, Amr
- Date
- 2019
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/171388
- Identifier
- vital:14364
- Identifier
-
https://doi.org/10.1109/ACCESS.2019.2960044
- Identifier
- ISBN:2169-3536
- Abstract
- Motifs have been recognized as basic network blocks and are found to be quite powerful in modeling certain patterns. Generally speaking, local characteristics of big networks could be reflected in network motifs. Over the years, motifs have attracted a lot of attention from researchers. However, most current literature reviews on motifs generally focus on the field of biological science. In contrast, here we try to present a comprehensive survey on motifs in the context of big networks. We introduce the definition of motifs and other related concepts. Big networks with motif-based structures are analyzed. Specifically, we respectively analyze four kinds of networks, including biological networks, social networks, academic networks, and infrastructure networks. We then examine methods for motif discovery, motif counting, and motif clustering. The applications of motifs in different areas have also been reviewed. Finally, some challenges and open issues in this direction are discussed. © 2013 IEEE.
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Relation
- IEEE Access Vol. 7, no. (2019), p. 183322-183338
- Rights
- http://creativecommons.org/licenses/by/4.0/
- Rights
- Copyright © The Authors. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/
- Rights
- Open Access
- Rights
- This metadata is freely available under a CCO license
- Subject
- 1201 Architecture; Motif clustering; Motif counting; Motif discovery; Network motif; Network science
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