We propose a simplified signed graph convolution network model called LightSGCN. Specifically, LightSGCN utilizes linear propagation based on the balance theory, a widely adopted social theory. Then, the linear combination of hidden representations at each layer is used as the final representations. WebTable 5: Ablation study on loss functions. - "SDGNN: Learning Node Representation for Signed Directed Networks"
LightSGCN Proceedings of the 45th International …
WebApr 20, 2024 · The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval ( SIGIR 2024) released the list of accepted papers. It contains a total of 115 papers incl. posters etc. related to recommender-systems. I assessed the papers based on the title, so chances are, I missed a few and the actual number is even higher. Web(SP) LightSGCN: Powering Signed Graph Convolution Network for Link Sign Prediction with Simplified Architecture Design Haoxin Liu (DEMO) QFinder: A Framework for Quantity-centric Ranking Satya Almasian, Milena Bruseva and Michael Gertz (DEMO) Quote Erat Demonstrandum: A Web Interface for Exploring the Quotebank Corpus radm matthew sibley
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WebJan 7, 2024 · This work proposes a simplified signed graph convolution network model called LightSGCN, which outperforms the state-of-the-art signed GNNs methods with significant improvement in the link sign prediction task and achieves more than 100X speedup over the most similar and simplest baseline. Expand. PDF. View 1 excerpt, cites … WebLightSGCN: Powering Signed Graph Convolution Network for Link Sign Prediction with Simplified Architecture Design Haoxin Liu . In Enrique Amigó , Pablo Castells , Julio … WebOct 10, 2024 · 1.实验结果表明,GCN中两种常见的设计,即特征转换和非线性激活,对协同过滤的效果没有积极影响 2.我们提出了LightGCN,它只包含GCN中最基本的组件以供推荐,从而大大简化了模型设计。 3.我们通过遵循相同的设置对LightGCN和NGCF进行了经验比较,并证明了改进。 在从技术和经验两个角度对LightGCN的合理性进行了深入分析。 2 准 … radm michael ryan