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Node classification in heterogeneous graphs, where nodes and/or edges have multiple types.

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An Attention-based Graph Neural Network for Heterogeneous Structural Learning

19 Dec 2019didi/hetsann

In this paper, we focus on graph representation learning of heterogeneous information network (HIN), in which various types of vertices are connected by various types of relations.

GRAPH EMBEDDING GRAPH REPRESENTATION LEARNING HETEROGENEOUS NODE CLASSIFICATION MULTI-TASK LEARNING

Heterogeneous Deep Graph Infomax

19 Nov 2019YuxiangRen/Heterogeneous-Deep-Graph-Infomax

The derived node representations can be used to serve various downstream tasks, such as node classification and node clustering.

CLASSIFICATION GRAPH REPRESENTATION LEARNING HETEROGENEOUS NODE CLASSIFICATION NODE CLUSTERING

Multi-Relational Classification via Bayesian Ranked Non-Linear Embeddings

The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’19) 2019 ahmedrashed-ml/BRNLE

The task of classifying multi-relational data spans a wide range of domains such as document classification in citation networks, classification of emails, and protein labeling in proteins interaction graphs.

CLASSIFICATION DOCUMENT CLASSIFICATION HETEROGENEOUS NODE CLASSIFICATION LINK PREDICTION