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.

This study compares the flows of mobile researchers and the number of publications in international collaboration within the context of scientific and economic capacities. The goal is to identify the convergence or discrepancy of countries in mobility and collaboration and determine the positions and relative influence of countries in both processes. Using affiliation data from scientific publications, we analyze the distributions and networks of collaboration and mobility and their structural differences. The results show that there is a significant relationship between the flow of mobile researchers and the capacity for publishing with foreign partners in the more prolific countries, although mobility is always lower than collaboration. Size matters and scientific relationship are highly resource-dependent. Advanced and Proficient countries accumulate the highest proportion of the mobile authors and international publications with an extremely low representation of mobility in Developing and Lagging countries. In addition, the placement of countries is not always consistent in both networks, revealing distinct roles of mobility and collaboration, with particular instability for lower income countries. The more resources available in a country (both scientific and economic) the greater the likelihood of attracting foreign partners and mobilizing human capital. The policy relevance of these structural differences are described and a brief description of the limitations and future research are provided.

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h i g h l i g h t s• The interaction between friendship network and information network in a multi-relation networked system is of interest to us. • An inverse investigation is presented to analyzing the effect of users' taste on friendship creation. • The behavioral information involving with popular objects in bipartite information network improves accuracy of friendship prediction.• The different usable information in bipartite information network is respectively used in friendship prediction and recommendation system. a b s t r a c tHomophily is a significant mechanism for link prediction in complex network, of which principle describes that people with similar profiles or experiences tend to tie with each other. In a multi-relationship network, friendship among people has been utilized to reinforce similarity of taste for recommendation system whose basic idea is similar to homophily, yet how the taste inversely affects friendship prediction is little discussed. This paper contributes to address the issue by analyzing two benchmark data sets both including user's behavioral information of taste and friendship based on the principle of homophily. It can be found that the creation of friendship tightly associates with personal taste. Especially, the behavioral information of taste involving with popular objects is much more effective to improve the performance of friendship prediction. However, this result seems to be contradictory to the finding in that the behavior information of taste involving with popular objects is redundant in recommendation system. We thus discuss this inconformity to comprehensively understand the correlation between them.