The proliferation of data in RDF format calls for efficient and scalable solutions for their
management. While scalability in the era of big data is a hard requirement, modern systems …

State-of-the-art distributed RDF systems partition data across multiple computer nodes
(workers). Some systems perform cheap hash partitioning, which may result in expensive …

Besides its NP-completeness, the strict constraints of subgraph isomorphism are making it
impractical for graph pattern matching (GPM) in the context of big data. As a result, relaxed …

RDF Database Systems is a cutting-edge guide that distills everything you need to know to
effectively use or design an RDF database. This book starts with the basics of linked open …

The emerging need for conducting complex analysis over big RDF datasets calls for scale-
out solutions that can harness a computing cluster to process big RDF datasets. Queries …

Abstract Context: Big Data systems are a class of software systems that ingest, store,
process and serve massive amounts of heterogeneous data, from multiple sources. Despite …

Graph data management concerns the research and development of powerful technologies
for storing, processing and analyzing large volumes of graph data. This chapter presents an …

We study the problem of optimizing one-time and continuous subgraph queries using the
new worst-case optimal join plans. Worst-case optimal plans evaluate queries by matching …

知识图谱是人工智能的重要基石. 各领域大规模知识图谱的构建和发布对知识图谱数据管理提出
了新的挑战. 以数据模型的结构和操作要素为主线, 对目前的知识图谱数据管理理论, 方法 …

RDF data are used to model knowledge in various areas such as life sciences, Semantic
Web, bioinformatics, and social graphs. The size of real RDF data reaches billions of triples …