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• W2135077600 abstract "Predicting missing links in networks plays a significant role in modern science. On the basis of structural similarity, our paper proposes a new node-similarity-based measure called biased resource allocation (BRA), which is motivated by the resource allocation (RA) measure. Comparisons between BRA and nine well-known node-similarity-based measures on five real networks indicate that BRA performs no worse than RA, which was the best node-similarity-based index in previous researches. Afterwards, based on localPath (LP) and Katz measure, we propose another two improved measures, named Im-LocalPath and Im-Katz respectively. Numerical results show that the prediction accuracy of both Im-LP and Im-Katz measure improve compared with the original LP and Katz measure. Finally, a new path-similarity-based measure and its improved measure, called LYU and Im-LYU measure, are proposed and especially, Im-LYU measure is shown to perform more remarkably than other mentioned measures." @default.
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• W2135077600 date "2015-05-25" @default.
• W2135077600 modified "2023-09-24" @default.
• W2135077600 title "Predicting missing links via structural similarity" @default.
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• W2135077600 doi "https://doi.org/10.1142/s0217979215500952" @default.
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