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OpenGraph: Towards Open Graph Foundation Models
March 5, 2024, 2:41 p.m. | Lianghao Xia, Ben Kao, Chao Huang
cs.LG updates on arXiv.org arxiv.org
Abstract: Graph learning has become indispensable for interpreting and harnessing relational data in diverse fields, ranging from recommendation systems to social network analysis. In this context, a variety of GNNs have emerged as promising methodologies for encoding the structural information of graphs. By effectively capturing the graph's underlying structure, these GNNs have shown great potential in enhancing performance in graph learning tasks, such as link prediction and node classification. However, despite their successes, a significant challenge …
abstract analysis arxiv become context cs.ai cs.lg cs.si data diverse encoding fields foundation gnns graph graph learning graphs information network recommendation recommendation systems relational social systems type
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