The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Link prediction in social networks: the state-of-the-art
Open accessAbstract
In social networks, link prediction predicts missing links in current networks and new or dissolution links in future networks, is important for mining and analyzing the evolution of social networks. In the past decade, many works have been done about the link prediction in social networks. The goal of this paper is to comprehensively review, analyze and discuss the state-of-the-art of the link prediction in social networks. A systematical category for link prediction techniques and problems is presented. Then link prediction techniques and problems are analyzed and discussed. Typical applications of link prediction are also addressed. Achievements and roadmaps of some active research groups are introduced. Finally, some future challenges of the link prediction in social networks are discussed.
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Cites
Hierarchical Organization of Modularity in Metabolic Networks
Ravasz, E., Somera, A. L., Mongru, D. A., Oltvai, Z. N., & Barabási, A.-L. (2002) · Science · doi:10.1126/science.1073374 · Cited by 4,224
Hierarchical structure and the prediction of missing links in networks
Clauset, A., Moore, C., & Newman, M. E. J. (2008) · Nature · doi:10.1038/nature06830 · Cited by 2,171
Exploiting place features in link prediction on location-based social networks
Scellato, S., Noulas, A., & Mascolo, C. (2011) · Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/2020408.2020575 · Cited by 522
Inferring social ties across heterogenous networks
Tang, J., Lou, T., & Kleinberg, J. (2012) · Proceedings of the fifth ACM international conference on Web search and data mining · doi:10.1145/2124295.2124382 · Cited by 289
Cited by
Machine learning algorithms for social media analysis: A survey
T.K., B., Annavarapu, C. S. R., & Bablani, A. (2021) · Computer Science Review · doi:10.1016/j.cosrev.2021.100395 · Cited by 276
Unveiling Scholarly Communities over Knowledge Graphs
Vahdati, S., Palma, G., Nath, R. J., Lange, C., Auer, S., & Vidal, M.-E. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-00066-0_9 · Cited by 16
Metadata
- Authors
- Wang, P., Xu, B., Wu, Y., & Zhou, X.
- Venue
- Science China Information Sciences
- Published
- 2014-12-03
- Volume
- 58
- Issue
- 1
- Pages
- 1-38
- ISSN
- 1869-1919 (ISSN-L)
- 1674-733X
- OpenAlex
- W2964126306
- Cited by
- 548
- References
- 4
- FWCI
- 20.88
- Type
- journal article
- Language
- en
- Open access
- green
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- Wang, P., Xu, B., Wu, Y., & Zhou, X. (2015). Link prediction in social networks: the state-of-the-art. Science China Information Sciences. https://doi.org/10.1007/s11432-014-5237-y
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