scholarly journals A Fast Incremental Algorithm for Managing the Execution of Dynamically Controllable Temporal Networks

2010 ◽  
Author(s):  
Luke Hunsberger
Keyword(s):  
Incremental Algorithm ◽  
Temporal Networks

Probabilistic Temporal Networks.

1996 ◽  
Author(s):  
Eugene Santos ◽  
Young Jr. ◽  
Joel D.
Keyword(s):  
Temporal Networks

scholarly journals Higher-order temporal network effects through triplet evolution

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qing Yao ◽  
Bingsheng Chen ◽  
Tim S. Evans ◽  
Kim Christensen
Keyword(s):  
Real World ◽  
Link Prediction ◽  
Higher Order ◽  
Prediction Algorithm ◽  
Interaction Patterns ◽  
Temporal Networks ◽  
World Systems ◽  
Order Interaction ◽  
Space And Time ◽  
Pairwise Interactions

AbstractWe study the evolution of networks through ‘triplets’—three-node graphlets. We develop a method to compute a transition matrix to describe the evolution of triplets in temporal networks. To identify the importance of higher-order interactions in the evolution of networks, we compare both artificial and real-world data to a model based on pairwise interactions only. The significant differences between the computed matrix and the calculated matrix from the fitted parameters demonstrate that non-pairwise interactions exist for various real-world systems in space and time, such as our data sets. Furthermore, this also reveals that different patterns of higher-order interaction are involved in different real-world situations. To test our approach, we then use these transition matrices as the basis of a link prediction algorithm. We investigate our algorithm’s performance on four temporal networks, comparing our approach against ten other link prediction methods. Our results show that higher-order interactions in both space and time play a crucial role in the evolution of networks as we find our method, along with two other methods based on non-local interactions, give the best overall performance. The results also confirm the concept that the higher-order interaction patterns, i.e., triplet dynamics, can help us understand and predict the evolution of different real-world systems.

scholarly journals Temporal gravity model for important node identification in temporal networks

2021 ◽  
Vol 147 ◽  
pp. 110934
Author(s):  
Jialin Bi ◽  
Ji Jin ◽  
Cunquan Qu ◽  
Xiuxiu Zhan ◽  
Guanghui Wang ◽  
...  
Keyword(s):  
Gravity Model ◽  
Temporal Networks ◽  
Temporal Gravity
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