And while graph neural networks have been used for supervised and unsupervised learning on networks, their application to modularity optimization has not been explored yet. This paper proposes a new variant of the recurrent graph neural network algorithm for unsupervised network community detection ...
论文: Overlapping Community Detection with Graph Neural Networks. 源码: https://github.com/shchur/overlapping-community-detection 文章概述 现有的用于社团检测的神经网络只检测不相交的社区,而真实的社区却是重叠的,针对这一不足,提出了一种基于GNN的重叠社区检测模型NOCD。文章... ...
J. Bruna and X. Li. Community Detection with Graph Neural Networks. arXiv preprint arXiv:1705....
In this paper, we first propose a graph neural network encoding method for multiobjective evolutionary algorithm to handle the community detection problem in complex attribute networks. In the graph neural network encoding method, each edge in an attribute network is associated with a continuous variab...
Graph Wavelet Neural Network Bingbing Xu, Huawei Shen, Qi Cao, Yunqi Qiu, Xueqi Cheng ICLR 2019 Supervised Community Detection with Line Graph Neural Networks Zhengdao Chen, Xiang Li, Joan Bruna ICLR 2019 Predict then Propagate: Graph Neural Networks meet Personalized PageRank ...
可以处理子图相关的问题：社区挖掘J. Bruna and X. Li. Community Detection with Graph Neural Network...
deep-learningtext-generationpytorchknowledge-graphrecommender-systemrecommendationpretrained-modelshuman-machine-interactiondialog-systemgraph-neural-networkconversational-recommendationconversation-system UpdatedApr 12, 2024 Python Deep and conventional community detection related papers, implementations, datasets, and too...
python setup.py install PyTorch 0.2.0 Python 3.6 cd multiscalegnn python snap.py --graph 'dblp' --data_dir './../data/' [1]J. Bruna and L. Li, Community Detection with Graph Neural Networks, 2017. [2]Stanford Network Analysis Project....
a graph neural network (GNN) based graph pattern matching approach that can match provenance data against known attack behaviors in a robust way. Specifically, we design a graph neural network architecture with two novel networks:attribute embedding networksthat could incorporate Indicators of Compromise...
competitive graph neural network (CGNN)-based fraud detection system (eFraudCom) 一种基于竞争图神经网络(CGNN)的欺诈检测系统(eFraudCom),以检测电子商务平台上的欺诈行为。CGNN是一个基于GCN的GAE系统。eFraudCom系统由数据处理器和欺诈检测器组成。具体而言,在数据处理器中,对代表性的正态数据进行采样,并...