论文标题
边缘知识图管理
Knowledge Graph Management on the Edge
论文作者
论文摘要
Edge Computing是一个创新的平台，用于需要低延迟决策的服务。它的成功部分取决于有效的数据管理系统的存在。我们认为，由于知识图管理系统的数据集成和推理功能，在此上下文中具有关键作用。在本文中，我们介绍了一种简洁的，一种紧凑，无解压缩的，自我索引，内存RDF商店，可以回答SPARQL查询，包括那些需要与某些本体论相关的推理服务的问题。在展示其在现实世界和合成数据集上的效率之前，我们会提供有关其设计和实施的详细信息。
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.
