Structure-oriented prediction in complex networks

Ren, Zhuo-Ming; Zeng, An; Zhang, Yicheng

doi:10.1016/j.physrep.2018.05.002

Cited by 44 publications

(17 citation statements)

References 347 publications

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“…Such inference is not the subject of this paper. Relevant discussions can be found in [ 29 , 30 ] for network modeling. Combination the inference of network and dynamics will be studied in future work.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Maximum Entropy Approach to Reliability of Multi-Component Systems with Non-Repairable or Repairable Components

Chen

Guan

et al. 2021

Entropy

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The degradation and recovery processes are multi-scale phenomena in many physical, engineering, biological, and social systems, and determine the aging of the entire system. Therefore, understanding the interplay between the two processes at the component level is the key to evaluate the reliability of the system. Based on the principle of maximum entropy, an approach is proposed to model and infer the processes at the component level, and is applied to repairable and non-repairable systems. By incorporating the reliability block diagram, this approach allows for integrating the information of network connectivity and statistical moments to infer the hazard or recovery rates of the degradation or recovery processes. The overall approach is demonstrated with numerical examples.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Maximum Entropy Approach to Reliability of Multi-Component Systems with Non-Repairable or Repairable Components

Chen

Guan

et al. 2021

Entropy

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“…The former contains 90% of links and the latter contains the remaining 10%. [36] is the most typical measure for performance evaluation in link prediction task. The value of AUC ranges from 0 to 1.…”

Section: B Datasetsmentioning

confidence: 99%

“…Precision [36] is defined as the ratio of correct prediction in the top L predicted links. If there are m correct links among the top L links, the precision is defined as:…”

Section: B Datasetsmentioning

confidence: 99%

A Quad Motifs Index for Directed Link Prediction

Liu

Chang

et al. 2019

IEEE Access

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Network motif is a sub-graph pattern may reflect structure functions or reveal underneath mechanics. Some scholars have used triadic motifs for link prediction and achieve convincing results. But most of them ignore the effectiveness of quad motifs in calculating the similarity of two endpoints. In this article, a new method based on quad motifs is proposed. Two winner motifs are chosen among 199 sub-graphs. Local information of motifs is also taken into consideration. Experiments on nine real networks show that the index we proposed can improve prediction accuracy, compared with seven wellknown measures. INDEX TERMS Link prediction, quad motifs, directed networks.

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“…The World Trade Network has attracted the attention of researchers in many fields and has become an important research field in studying the economic development of countries. By studying the structure and dynamics of trade networks, physicists have made it possible to explain the state of development and potential of the country’s economy from the complex interactions among nations [ 1 ]. Hausmann and Hidalgo et al [ 2 , 3 ] proposed the Economic Complexity Index (ECI) to measure diversification of a country and the ubiquity of a product.…”

Section: Introductionmentioning

confidence: 99%

Industry Upgrading: Recommendations of New Products Based on World Trade Network

Zhang

Chen

Kong

et al. 2019

Entropy

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GDP is a classic indicator of the extent of national economic development. Research based on the World Trade Network has found that a country’s GDP depends largely on the products it exports. In order to increase the competitiveness of a country and further increase its GDP, a crucial issue is finding the right direction to upgrade the industry so that the country can enhance its competitiveness. The proximity indicator measures the similarity between products and can be used to predict the probability that a country will develop a new industry. On the other hand, the Fitness–Complexity algorithm can help to find the important products and developing countries. In this paper, we find that the maximum of the proximity between a certain product and a country’s existing products is highly correlated with the probability that the country exports this new product in the next year. In addition, we find that the more products that are related to a certain product, the higher probability of the emergence of the new product. Finally, we combine the proximity indicator and the Fitness–Complexity algorithm and then attempt to provide a recommendation list of new products that can help developing countries to upgrade their industry. A few examples are given in the end.

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Structure-oriented prediction in complex networks

Cited by 44 publications

References 347 publications

Maximum Entropy Approach to Reliability of Multi-Component Systems with Non-Repairable or Repairable Components

Maximum Entropy Approach to Reliability of Multi-Component Systems with Non-Repairable or Repairable Components

A Quad Motifs Index for Directed Link Prediction

Industry Upgrading: Recommendations of New Products Based on World Trade Network

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