So sánh phương pháp

	DBSCAN	Mạng Hồi quy Đồ thị (Graph Attention Network - GAT)
Lĩnh vực	Học máy	Học sâu
Họ	Machine learning	Machine learning
Năm ra đời	1996	2018
Người khởi xướng	Ester, M., Kriegel, H.-P., Sander, J. & Xu, X.	Veličković, P. et al.
Loại	Density-based clustering algorithm	Graph neural network (attention-based)
Công trình gốc	Ester, M., Kriegel, H.-P., Sander, J. & Xu, X. (1996). A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise. Proceedings of the 2nd KDD, 226–231.	Veličković, P. et al. (2018). Graph Attention Networks. ICLR.
Tên gọi khác	DBSCAN Kümeleme, density-based clustering, density-based spatial clustering	Graf Dikkat Ağı (GAT), GAT, graph attention network, attention-based graph neural network
Liên quan	3	4
Tóm tắt	DBSCAN is a density-based clustering algorithm, introduced by Ester, Kriegel, Sander and Xu in 1996, that groups together points lying in dense regions and flags points in sparse regions as noise. It is effective on noisy data and on clusters of irregular, non-spherical shapes.	The Graph Attention Network (GAT), introduced by Veličković and colleagues in 2018, is a graph neural network variant that learns how much importance to assign to each neighbouring node through a self-attention mechanism. On heterogeneous neighbourhoods and relational classification it produces results superior to graph convolutional networks (GCN).