title: Prediction of Links and Weights in Networks by Reliable Routes.
abstract: Link prediction aims to uncover missing links or predict the emergence of future relationships from the current network structure. Plenty of algorithms have been developed for link prediction in unweighted networks, but only a few have been extended to weighted networks. In this paper, we present what we call a "reliable-route method" to extend unweighted local similarity indices to weighted ones. Using these indices, we can predict both the existence of links and their weights. Experiments on various real-world networks suggest that our reliable-route weighted resource-allocation index performs noticeably better than others with respect to weight prediction. For existence prediction it is either the highest or very close to the highest. Further analysis shows a strong positive correlation between the clustering coefficient and prediction accuracy. Finally, we apply our method to the prediction of missing protein-protein interactions and their confidence scores from known PPI networks. Once again, our reliable-route method shows the highest accuracy.
authors.affiliation: Department of Mathematics, Logistical Engineering University, Chongqing, China.
authors.forename: Jing
authors.initials: J
authors.lastname: Zhao
authors.affiliation: CompleX Lab, Web Sciences Center, University of Electronic Science and Technology of China, Chengdu, China.
authors.forename: Lili
authors.initials: L
authors.lastname: Miao
authors.affiliation: Department of Mathematics, Logistical Engineering University, Chongqing, China.
authors.forename: Jian
authors.initials: J
authors.lastname: Yang
authors.affiliation: Department of Mathematics, Logistical Engineering University, Chongqing, China.
authors.forename: Haiyang
authors.initials: H
authors.lastname: Fang
authors.affiliation: CompleX Lab, Web Sciences Center, University of Electronic Science and Technology of China, Chengdu, China.
authors.forename: Qian-Ming
authors.initials: QM
authors.lastname: Zhang
authors.affiliation: CompleX Lab, Web Sciences Center, University of Electronic Science and Technology of China, Chengdu, China.
authors.forename: Min
authors.initials: M
authors.lastname: Nie
authors.affiliation: Department of Energy Science, Sungkyunkwan University, Suwon, Korea.
authors.forename: Petter
authors.initials: P
authors.lastname: Holme
authors.affiliation: 1] CompleX Lab, Web Sciences Center, University of Electronic Science and Technology of China, Chengdu, China [2] Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China.
authors.forename: Tao
authors.initials: T
authors.lastname: Zhou
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D006801:Humans; D025941:Protein Interaction Mapping / Q000379:methods*