Attributed Network

Attributed networks, which incorporate both relational (network structure) and descriptive (node attributes) data, are increasingly studied to improve tasks like community detection and anomaly identification. Current research focuses on developing sophisticated algorithms, often leveraging graph neural networks (GNNs) and autoencoders, to effectively integrate these dual data sources, addressing challenges like handling high-dimensional attributes and higher-order network structures. These advancements have significant implications for diverse fields, enabling improved analysis of complex systems in areas such as social networks, bioinformatics, and fraud detection.

Papers

August 10, 2024

A Versatile Framework for Attributed Network Clustering via K-Nearest Neighbor Augmentation
Yiran Li, Gongyao Guo, Jieming Shi, Renchi Yang, Shiqi Shen, Qing Li, Jun Luo
Graph Clustering Attributed Network Node Clustering Multiplex Graph Network Clustering

July 9, 2024

Changepoint Detection in Highly-Attributed Dynamic Graphs
Emiliano Penaloza, Nathaniel Stevens
Graph Neural Network Change Point Detection Dynamic Network Attributed Network

June 7, 2024

Higher-order Structure Based Anomaly Detection on Attributed Networks
Xu Yuan, Na Zhou, Shuo Yu, Huafei Huang, Zhikui Chen, Feng Xia
Anomaly Detection Higher Order Higher Order Network Attributed Network

January 3, 2024

SCALA: Sparsification-based Contrastive Learning for Anomaly Detection on Attributed Networks
Enbo He, Yitong Hao, Yue Zhang, Guisheng Yin, Lina Yao
Contrastive Learning Anomaly Detection Node Representation Anomaly Score interactiOn Pattern Attributed Network Anomaly Node

November 21, 2023

Unsupervised Graph Attention Autoencoder for Attributed Networks using K-means Loss
Abdelfateh Bekkair, Slimane Bellaouar, Slimane Oulad-Naoui
Graph Neural Network Community Detection Graph Attention Community Structure Social Network Analysis Attributed Network

October 30, 2023

Exact Recovery and Bregman Hard Clustering of Node-Attributed Stochastic Block Model
Maximilien Dreveton, Felipe S. Fernandes, Daniel R. Figueiredo
Sparse Network Stochastic Block Model Hard Clustering Interaction Network Attributed Network Exact Community Recovery Iterative Clustering

September 27, 2023

SANGEA: Scalable and Attributed Network Generation
Valentin Lemaire, Youssef Achenchabe, Lucas Ody, Houssem Eddine Souid, Gianmarco Aversano, Nicolas Posocco, Sabri Skhiri
Large Graph Synthetic Graph Attributed Network

July 22, 2023

Collaborative Graph Neural Networks for Attributed Network Embedding
Qiaoyu Tan, Xin Zhang, Xiao Huang, Hao Chen, Jundong Li, Xia Hu
Graph Neural Network Graph Convolution GNN Architecture Attributed Network Attribute Aware Network

February 9, 2023

Privacy-Preserving Representation Learning for Text-Attributed Networks with Simplicial Complexes
Huixin Zhan, Victor S. Sheng
Neural Network Representation Learning Simplicial Complex Network Representation Attributed Network

November 28, 2022

ARISE: Graph Anomaly Detection on Attributed Networks via Substructure Awareness
Jingcan Duan, Bin Xiao, Siwei Wang, Haifang Zhou, Xinwang Liu
Graph Anomaly Detection Attributed Network Network Anomaly Detection ApeRIodic SEmi Parametric Anomaly Node Topology Attack

September 20, 2022

Attributed Network Embedding Model for Exposing COVID-19 Spread Trajectory Archetypes
Junwei Ma, Bo Li, Qingchun Li, Chao Fan, Ali Mostafavi
Full Model Epidemic Forecasting Attributed Network Spread Trajectory

July 8, 2022

GCN-based Multi-task Representation Learning for Anomaly Detection in Attributed Networks
Venus Haghighi, Behnaz Soltani, Adnan Mahmood, Quan Z. Sheng, Jian Yang
Anomaly Detection Multi Task Learning Community Detection Based Anomaly Detection Multi View Representation Learning Multi Task Representation Attributed Network

June 21, 2022

Propagation with Adaptive Mask then Training for Node Classification on Attributed Networks
Jinsong Chen, Boyu Li, Qiuting He, Kun He
Training Data Node Classification Fast Propagation Graph Propagation Attributed Network Adaptive Mask

May 28, 2022

Deep Embedded Clustering with Distribution Consistency Preservation for Attributed Networks
Yimei Zheng, Caiyan Jia, Jian Yu, Xuanya Li
Node Representation Deep Clustering Graph AutoEncoder Graph Autoencoders Attributed Network Latent Consistency Model Distribution Consistency

May 27, 2022

FadMan: Federated Anomaly Detection across Multiple Attributed Networks
Nannan Wu, Ning Zhang, Wenjun Wang, Lixin Fan, Qiang Yang
Anomaly Detection Anomalous Graph Attributed Network

May 10, 2022

Reconstruction Enhanced Multi-View Contrastive Learning for Anomaly Detection on Attributed Networks
Jiaqiang Zhang, Senzhang Wang, Songcan Chen
Contrastive Learning Anomaly Detection Self Supervised Learning Framework Multi View Contrastive Learning Attributed Network Anomaly Node Level Consistency

February 13, 2022

Learning Asymmetric Embedding for Attributed Networks via Convolutional Neural Network
Mohammadreza Radmanesh, Hossein Ghorbanzadeh, Ahmad Asgharian Rezaei, Mahdi Jalili, Xinghuo Yu
Convolutional Neural Network Node Classification Attributed Network Asymmetric Learning Asymmetric Similarity

January 8, 2022

AnomMAN: Detect Anomaly on Multi-view Attributed Networks
Ling-Hao Chen, He Li, Wanyuan Zhang, Jianbin Huang, Xiaoke Ma, Jiangtao Cui, Ning Li, Jaesoo Yoo
Anomaly Detection Graph Convolution Unlabeled Anomaly Attributed Network

November 4, 2021

Measuring Proximity in Attributed Networks for Community Detection
Rinat Aynulin, Pavel Chebotarev
Community Detection Spectral Clustering Similarity Measure Network Analysis Proximity Search Attributed Network

Attributed Network

Papers

A Versatile Framework for Attributed Network Clustering via K-Nearest Neighbor Augmentation

Changepoint Detection in Highly-Attributed Dynamic Graphs

Higher-order Structure Based Anomaly Detection on Attributed Networks

SCALA: Sparsification-based Contrastive Learning for Anomaly Detection on Attributed Networks

Unsupervised Graph Attention Autoencoder for Attributed Networks using K-means Loss

Exact Recovery and Bregman Hard Clustering of Node-Attributed Stochastic Block Model

SANGEA: Scalable and Attributed Network Generation

Collaborative Graph Neural Networks for Attributed Network Embedding

Privacy-Preserving Representation Learning for Text-Attributed Networks with Simplicial Complexes

ARISE: Graph Anomaly Detection on Attributed Networks via Substructure Awareness

Attributed Network Embedding Model for Exposing COVID-19 Spread Trajectory Archetypes

GCN-based Multi-task Representation Learning for Anomaly Detection in Attributed Networks

Propagation with Adaptive Mask then Training for Node Classification on Attributed Networks

Deep Embedded Clustering with Distribution Consistency Preservation for Attributed Networks

FadMan: Federated Anomaly Detection across Multiple Attributed Networks

Reconstruction Enhanced Multi-View Contrastive Learning for Anomaly Detection on Attributed Networks

Learning Asymmetric Embedding for Attributed Networks via Convolutional Neural Network

AnomMAN: Detect Anomaly on Multi-view Attributed Networks

Measuring Proximity in Attributed Networks for Community Detection