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Vital nodes identification in complex networks
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The H-index of a network node and its relation to degree and coreness
TLDR
A family of H-indices are obtained that can be used to measure a node's importance and it is proved that the convergence to coreness can be guaranteed even under an asynchronous updating process, allowing a decentralized local method of calculating a nodes' coreness in large-scale evolving networks.
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Link prediction in complex networks: A local naïve Bayes model
TLDR
It is argued that different common neighbors may play different roles and thus contributes differently, and a local naïve Bayes model is proposed, which can provide more accurate predictions.
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Potential Theory for Directed Networks
TLDR
A new mechanism for the local organization of directed networks is proposed, which assumes that every directed link corresponds to a decrease of a unit potential and subgraphs with definable potential values for all nodes are preferred.
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Geography and Similarity of Regional Cuisines in China
TLDR
An online database documenting recipes from various Chinese regional cuisines is harnessed and a model of regional cuisine evolution is developed that provides helpful clues for understanding the evolution of cuisine and cultures.
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Evaluating network models: A likelihood analysis
TLDR
The results suggest that the Generalized Linear Preferential (GLP) model outperforms the Tel Aviv Network Generator (Tang), while both two models are better than the Barabási-Albert (BA) and Erdös-Rényi (ER) models.
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Prediction of Links and Weights in Networks by Reliable Routes
  • Jing ZhaoLili Miao T. Zhou
  • Computer Science
    Scientific reports
  • 22 July 2015
TLDR
A “reliable-route method” to extend unweighted local similarity indices to weighted ones that can predict both the existence of links and their weights and applies this method to the prediction of missing protein-protein interactions and their confidence scores from known PPI networks.
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Measuring multiple evolution mechanisms of complex networks
TLDR
This study introduces two methods (link prediction and likelihood analysis) to measure multiple evolution mechanisms of complex networks and applies this method to some real-world networks, to see how popularity and clustering co-evolve.
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Segregation in religion networks
TLDR
A directed social network extracted from weibo.com, which is consisted of 6875 believers in Christianity, Buddhism, Islam and Taoism, is analyzed to provide quantitative insights into religious segregation and valuable evidence for religious syncretism.
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Recommending investors for new startups by integrating network diffusion and investors' domain preference
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