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Awesome-Multi-View-Graph-Clustering

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Welcome to the Awesome Multi-View Graph Clustering repository! This is a curated collection of resources, papers, and methodologies dedicated to Multi-View Graph Clustering in complex networks. Multi-view graph clustering, an advanced form of graph clustering, leverages multiple perspectives or views of data to reveal hidden structures and communities within networks. This repository aims to be a comprehensive guide for researchers and practitioners exploring this fascinating area, covering a wide range of topics from foundational theories to state-of-the-art techniques.

Multi-view graph clustering is pivotal for understanding complex systems where entities interact in multiple contexts, such as:

  • Social Networks: Analyzing diverse interactions like friendships, professional connections, and shared interests to better understand community structures.
  • Biological Networks: Integrating various biological interactions, such as gene regulation, protein-protein interactions, and metabolic pathways, to uncover functional modules.
  • Communication Networks: Studying different types of communications, such as email exchanges and social media interactions, to detect underlying group dynamics.

Whether you are a researcher looking to delve into the nuances of multi-view graph clustering, a practitioner seeking to apply these techniques to real-world problems, or a student eager to learn about this cutting-edge field, this repository is your go-to resource for everything multi-view graph clustering!


📚 Contents


📑 Papers

Multi-view graph clustering

Year Title CA Institution Venue Paper Code
2024 Dual Information Enhanced Multi-view Attributed Graph Clustering Chang-Dong Wang Sun Yat-sen University TNNLS Link Link
2024 Graph ClusteringContrastive Multiview Attribute Graph Clustering With Adaptive Encoders Chang-Dong Wang Sun Yat-sen University TNNLS Link --
2024 Multi-view attributed graph clustering based on graph diffusion convolution with adaptive fusion Zhi hong Zhang Zhengzhou University ESWA Link --
2024 Scalable and Structural Multi-view Graph Clustering with Adaptive Anchor Fusion Xinwang Liu National University of Defense Technology TIP Link Link
2024 Multi-view fair-augmentation contrastive graph clustering with reliable pseudo-labels Wei Xu Renmin University IS Link Link
2023 Sample-level Multi-view Graph Clustering Shudong Huang Sichuan University CVPR Link Link
2023 Metric Multi-View Graph Clustering Shudong Huang Sichuan University AAAI Link Link
2023 Clustering Information-guided Multi-view Contrastive Graph Clustering Jinke Wang Henan University ICPADS Link Link
2023 Simultaneous linear multi-view attributed graph representation learning and clustering Mohamed Nadif Université Paris Cité WSDM Link Link
2023 Deep multi-view graph clustering network with weighting mechanism and collaborative training Fuyuan Cao Shanxi University ESWA Link --
2021 Multi-view Contrastive Graph Clustering Zhao Kang University of Electronic Science and Technology of China NIPS Link Link
2021 Graph Filter-based Multi-view Attributed Graph Clustering Zhao Kang University of Electronic Science and Technology of China IJCAI Link Link
2021 Multi-view Attributed Graph Clustering Zhao Kang University of Electronic Science and Technology of China TKDE Link Link
2020 Multi-View Attribute Graph Convolution Networks for Clustering Quanxue Gao Xidian University IJCAI Link Link
2019 Contextual Correlation Preserving Multiview Featured Graph Clustering Yang Liu Hong Kong Baptist Universit TCYB Link Link

🏷️ Datasets

Links to publicly available multi-view graph datasets, including descriptions and recommended use cases.

Datasets Views Nodes Edges Attribute content Features dimensions Clusters Link
ACM 2 3025 Co-Subject (29,281)|Co-Author (2,210,761) Keywords of the paper 1830 3 Link
DBLP 3 4057 Co-Author (11,113)|Co-Conference (5,000,495)|Co-Term (6,776,335) Keywords of the author 334 4 Link
IMDB 2 4780 Co-Actor (98,010)|Co-Director (21,018) Keywords of the movie plot 1232 3 Link
Cornell 2 183 295 The bag-of-words representation of the corresponding page 1703 5 Link Link
Wisconsin 2 251 499 The bag-of-words representation of the corresponding page 1703 5 Link Link

"useful-libraries"> 📖 Useful Libraries


Happy researching! If you find this repository useful, feel free to star ⭐ it and contribute.

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