论文标题
属性丰富的事件驱动图的层次结构实体对齐
Hierarchical Entity Alignment for Attribute-Rich Event-Driven Graphs
论文作者
论文摘要
本文解决了属性丰富的事件驱动图中实体对齐的问题。与许多其他实体一致性问题不同，我们对基于其行为的相似性（即参加类似事件的实体的相似性）对齐实体感兴趣。我们将该问题的生成过程建模为贝叶斯模型，并从后验预测分布中得出我们提出的算法。我们将分层实体对齐（热）算法应用于两个数据集，一个在出版物上，另一个是在金融交易上，该数据集源自真实数据，并由外部合作者提供给我们。
This paper addresses the problem of entity alignment in attribute-rich event-driven graphs. Unlike many other entity alignment problems, we are interested in aligning entities based on the similarity of their actions, i.e., entities that participate in similar events are more likely to be the same. We model the generative process of this problem as a Bayesian model and derive our proposed algorithm from the posterior predictive distribution. We apply our Hierarchical Entity AlignmenT (HEAT) algorithm to two datasets, one on publications and the other on financial transactions, derived from real data and provided to us by an external collaborator.
