Dynamic Backup Algorithm of Network Resources Based on Node Characteristics Under Network Slicing

Wang, Xuan; Han, Ziyuan; Qin, Jingyao

doi:10.1007/978-3-031-06764-8_52

Cited by 1 publication

(1 citation statement)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…But is rarely seen in the field of technological innovation collaboration. The author's previous research found that from the structural characteristics of the technological innovation cooperation network, the links in this network can be predicted, and the existing classical link prediction methods can reach more than 90% in the AUC index, but only up to 8.5% in the Precision index 8 . However, the Precision metric is of great practical value for the recommendation of technological innovation partners, and it is not known whether the prediction accuracy achieved so far is the limit of the network.…”

Section: Introductionmentioning

confidence: 99%

Research on Predictability of Technological Innovation Cooperation Network Links in offshore engineering equipment

Sun,

Wang

2024

Preprint

View full text Add to dashboard Cite

This paper amis to provide support for the prediction and recommendation of technological innovation cooperation relations. A patent-based offshore engineering equipment technological innovation cooperation network is built at first. The trend of network predictability and its upper limit are explored through the normalized shortest compression length of the network structure, and the actual prediction accuracy of classical link prediction methods is compared with the upper limit. Results show that the change of normalized shortest compression length of the network structure is fully consistent with the development trend of the link predictability of offshore engineering equipment technological innovation cooperation network, and the normalized shortest compression length can also be used as the basis for quantitative characterization of the upper limit of network link predictability. Futhermore, the prediction accuracy of the classical link prediction methods is about 30% lower than the upper limit calculated according to the normalized shortest compression length.

show abstract

Section: Introductionmentioning

confidence: 99%