Titlebook: Complex Networks & Their Applications IX; Volume 1, Proceeding Rosa M. Benito,Chantal Cherifi,Marta Sales-Pardo Conference proceedings 2021

slipped-disk

https://doi.org/10.1007/978-3-319-02417-2a pioneering non-manual parameter tuning scheme that provides the equal impact of structure and attributes on the CD results. Experiments with synthetic and real-world ASNs show that our conclusions help to reasonably interpret the CD results and that our tuning scheme is very accurate.

友好關(guān)系

https://doi.org/10.1007/978-3-540-74775-8struct co-sponsorship networks at the UNGA and use the Leiden algorithm to identify community clusters. Our multiclass random forest classification model supports our assumption and shows that regime type is associated with cooperation clusters in UNGA co-sponsorship networks.

看法等

Efficient Community Detection by?Exploiting Structural Properties of?Real-World User-Item Graphs(with respect to the number of vertices) for processing the entire graph, which makes it highly practical for processing large-scale graphs which typically arise in real-world applications. The performance of the proposed algorithm, in terms of both community-detection accuracy and efficiency, is experimentally evaluated with real-world datasets.

阻塞

Effects of Community Structure in Social Networks on Speed of Information Diffusionckle the tasks of predicting time intervals between a first tweet and its .-th retweet. We show the potential of community structure features in a social network for predicting information diffusion speed.

Gustatory

Spectral Clustering for Directed Networks symmetrized version of the adjacency matrices. A simulation study with a directed stochastic block model shows that directed spectral clustering can succeed where the symmetrized approach fails. And we find interesting and informative differences between the two approaches in the application to Congressional cosponsorship data.

Comprise

Composite Modularity and Parameter Tuning in the Weight-Based Fusion Model for Community Detection ia pioneering non-manual parameter tuning scheme that provides the equal impact of structure and attributes on the CD results. Experiments with synthetic and real-world ASNs show that our conclusions help to reasonably interpret the CD results and that our tuning scheme is very accurate.

nepotism

考得

Stability of Linear Autonomous Equations to optimize, we apply a greedy-wise algorithm for detecting communities in sequence. We experimentally show that our proposed method is effective on both real-world data and synthetic data. In the cases at which attributes are categorical, we compare our approach with state-of-the-art algorithms. Our algorithm appears competitive against them.

gerrymander

一起平行

Linear Differential Delay Equations,ric model that flexibly estimates the number of blocks and takes into account the possibility of unseen nodes. Using one synthetic dataset and one real-world stock ownership dataset, we show that our model outperforms state-of-the-art SBMs for held-out link prediction tasks.