Keys for graphs uses the topology and value constraints needed to uniquely identify entities in a graph database. They have been studied to support object identification, knowledge fusion, data deduplication, and social network reconciliation. In this paper, we present our algorithm to mine keys over graphs. Our algorithm discovers keys in a graph via frequent subgraph expansion. We present two properties that define a meaningful key, including minimality and support. Lastly, using real-world graphs, we experimentally verify the efficiency of our algorithm on real world graphs.

翻译：图形的密钥使用在图形数据库中独特识别实体所需的地形学和价值限制。 已经研究过它们以支持对象识别、 知识聚合、 数据重复和社会网络对等。 在本文中, 我们将我们的算法展示给图形中的密钥。 我们的算法通过频繁的子图扩展在图表中发现密钥。 我们展示了两个属性, 来定义一个有意义的关键, 包括最小值和支持。 最后, 我们用真实世界的图表, 实验地验证了真实世界图形中的算法效率 。