协作双聚合用于定向图嵌入
Linsong Liu1, Ke-Jia Chen2, Zheng Liu2
1School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, 210023, Jiangsu, China.
概括
本研究介绍了用于定向图嵌入的协作双向聚合方法 (COBA). COBA有效地解决了低度节点的挑战,在图形分析任务中表现优于现有的方法.
科学领域:
- 计算机科学 计算机科学
- 图形理论 图形理论
- 机器学习 机器学习
背景情况:
- 定向图形模拟非对称关系,对于图形分析至关重要.
- 当前的定向图嵌入方法在稀疏图中与低/零进/出度节点作斗争.
研究的目的:
- 提出一种新的协作双向聚合方法 (COBA),用于定向图嵌入.
- 增强对连接有限的节点的表示学习.
主要方法:
- COBA 汇总了来自邻国的源/目标嵌入.
- 它特别增强了使用相反方向邻居的零进出度节点.
- 源和目标嵌入式与协作聚合相关.
主要成果:
- 理论分析证实了COBA的可行性和合理性.
- 实验表明,COBA在多个任务上优于最先进的方法.
- 建议的聚合策略的有效性得到了验证.
结论:
- 科巴为定向图嵌入提供了一个强大的解决方案,特别是在稀疏图中.
- 该方法提高了下游图形分析和推理能力.
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