边缘知识图谱管理
Knowledge Graph Management on the Edge
摘要：
边缘计算作为一种创新平台出现，用于需要低延迟决策的服务。其成功部分取决于是否存在有效的数据管理系统。我们认为，知识图谱管理系统在这方面发挥了关键作用，由于其数据集成和推理功能。在本文中，我们提出了SuccinctEdge，一个紧凑的，无解压缩，自索引，内存中的RDF存储，可以回答SPARQL查询，包括那些需要推理服务相关联的一些本体。在展示其在真实世界和合成数据集上的效率之前，我们提供了有关其设计和实现的详细信息。
英文摘要：
Edge computing emerges as an innovative platform for services requiring low latency decision making. Its success partly depends on the existence of efficient data management systems. We consider that knowledge graph management systems have a key role to play in this context due to their data integration and reasoning features. In this paper, we present SuccinctEdge, a compact, decompression-free, self-index, in-memory RDF store that can answer SPARQL queries, including those requiring reasoning services associated to some ontology. We provide details on its design and implementation before demonstrating its efficiency on real-world and synthetic datasets.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
