Supervised and extended restart in random walks for ranking and link prediction in networks
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DOI: 10.1371/journal.pone.0213857
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Cited by:
- Tofighy, Sajjad & Charkari, Nasrollah Moghadam & Ghaderi, Foad, 2022. "Link prediction in multiplex networks using intralayer probabilistic distance and interlayer co-evolving factors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
- Davide Buffelli & Fabio Vandin, 2022. "The Impact of Global Structural Information in Graph Neural Networks Applications," Data, MDPI, vol. 7(1), pages 1-20, January.
- Zhou, Yinzuo & Wu, Chencheng & Tan, Lulu, 2021. "Biased random walk with restart for link prediction with graph embedding method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
- Liu, Yanyan & Li, Keping & Yan, Dongyang, 2024. "Quantification analysis of potential risk in railway accidents: A new random walk based approach," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
- Chao Li & Qiming Yang & Bowen Pang & Tiance Chen & Qian Cheng & Jiaomin Liu, 2021. "A Mixed Strategy of Higher-Order Structure for Link Prediction Problem on Bipartite Graphs," Mathematics, MDPI, vol. 9(24), pages 1-13, December.
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