Relation Structure|Aware Heterogeneous Graph Neural Network

Relation Structure-Aware Heterogeneous Graph Neural Network

A unified model that integrates graph and its coarsened line graph to embed both nodes and edges in heterogeneous graphs without requiring any prior knowledge.

Relation Structure-Aware Heterogeneous Graph Neural Network

In this paper, we propose. Relation Structure-Aware Heterogeneous Graph Neural Network. (RSHN), a unified model that integrates graph and its coarsened line ...

RHCO: A Relation-aware Heterogeneous Graph Neural Network ...

We propose a novel Relation-aware Heterogeneous Graph Neural Network with Contrastive Learning (RHCO) for large-scale heterogeneous graph representation ...

SHGNN: Structure-Aware Heterogeneous Graph Neural Network

Many real-world graphs (networks) are heterogeneous with different types of nodes and edges. Heterogeneous graph embedding, aiming at learning ...

(PDF) Relation Structure-Aware Heterogeneous Graph Neural ...

To tackle the heterogeneity of edge connections, RSHN first creates a Coarsened Line Graph Neural Network (CL-GNN) to excavate edge-centric relation structural ...

Relation-aware heterogeneous graph neural network for entity ...

This may lead to poor performance on entity alignment with similar structures. The two entities in Fig. 2 have the same structure, and the two ...

Relation Structure-Aware Heterogeneous Graph Neural Network

To tackle the heterogeneity of edge connections, RSHN first creates a Coarsened Line Graph Neural Network (CL-GNN) to excavate edge-centric relation structural ...

Relation Structure-Aware Heterogeneous Graph Neural Network

In this paper, we propose Relation Structure-Aware Heterogeneous Graph Neural Network (RSHN), a unified model that integrates graph and its coarsened line graph ...

Relation Structure-Aware Hierarchical Heterogeneous Graph ...

Wang, Relation structure-aware heterogeneous graph neural network, in Proc. IEEE Int. Conf. Data Mining (ICDM ), Beijing, China, 2019, pp ...

[PDF] Relation Structure-Aware Heterogeneous Graph Neural Network

This paper proposes a Relation-aware Heterogeneous Graph Neural Network, namely R-HGNN, to learn node representations on heterogeneous graphs at a fine-grained ...

Zehong-Wang/SR-HGN - GitHub

This repo is for source code of Expert Systems with Applications paper "SR-HGN: Semantic-and Relation-Aware Heterogeneous Graph Neural Network".

Relation-Aware Heterogeneous Graph Neural Network for Fraud ...

1, there are three types of nodes in financial fraud detection tasks. Most GNNs assume a homogeneous graph structure, oversimplifying real-life ...

Relation-Aware Heterogeneous Graph Neural Network for Fraud ...

This paper introduces a novel approach for fraud detection using a Relation-Aware Heterogeneous Graph Neural Network (RHGNN) model

SHGNN: Structure-Aware Heterogeneous Graph Neural Network

A novel Structure-Aware Heterogeneous Graph Neural Network (SHGNN) is proposed to address the above limitations and achieves state-of-the-art results on the ...

Unbiased Heterogeneous Scene Graph Generation with Relation ...

We devise a novel message passing layer, called relation-aware message passing neural network (RMP), that aggregates the contextual information of an image ...

Heterogeneous Graph Structure Learning for Graph Neural Networks

Specifically, for each relation, three types of candidate graphs, i.e. the feature similarity graph, feature propagation graphs and semantic graphs, are ...

Descent Steps of a Relation-Aware Energy Produce Heterogeneous ...

Heterogeneous graph neural networks (GNNs) achieve strong performance on node classification tasks in a semi-supervised learning setting. However, as in the.

Descent Steps of a Relation-Aware Energy Produce Heterogeneous ...

Abstract. Heterogeneous graph neural networks (GNNs) achieve strong performance on node classification tasks in a semi-supervised learning setting. However, as ...

Heterogeneous Graph Neural Networks

... learning node embed- dings. RSHN (Zhu et al, 2019d) uses both original node graph and coarsened line graph to design a relation-structure aware HGNN. RGCN ...

Topic-aware Heterogeneous Graph Neural Network for Link Prediction

Heterogeneous graphs (HGs), consisting of multiple types of nodes and links, can characterize a variety of real-world complex systems.