R2DB: A System for Querying and Visualizing Weighted RDF Graphs

Songling Liu, J. P. Cedeño, K. Candan, M. Sapino, Shengyu Huang, Xinsheng Li
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引用次数: 9

Abstract

Existing RDF query languages and RDF stores fail to support a large class of knowledge applications which associate utilities or costs on the available knowledge statements. A recent proposal includes (a) a ranked RDF (R2DF) specification to enhance RDF triples with an application specific weights and (b) a SPA Rank QL query language specification, which provides novel primitives on top of the SPARQL language to express top-k queries using traditional query patterns as well as novel flexible path predicates. We introduce and demonstrate R2DB, a database system for querying weighted RDF graphs. R2DB relies on the AR2Q query processing engine, which leverages novel index structures to support efficient ranked path search and includes query optimization strategies based on proximity and sub-result inter-arrival times. In addition to being the first data management system for the R2DF data model, R2DB also provides an innovative features-of-interest (FoI) based method for visualizing large sets of query results (i.e., sub graphs of the data graph).
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R2DB:用于查询和可视化加权RDF图的系统
现有的RDF查询语言和RDF存储不能支持大量与可用知识语句相关的实用程序或成本的知识应用程序。最近的一项建议包括(A)一个排序RDF (R2DF)规范,用特定于应用程序的权重增强RDF三元组;(b)一个SPA Rank QL查询语言规范,它在SPARQL语言之上提供新颖的原语,使用传统的查询模式和新颖的灵活路径谓词来表达top-k查询。我们介绍并演示了R2DB,一个用于查询加权RDF图的数据库系统。R2DB依赖于AR2Q查询处理引擎,该引擎利用新颖的索引结构来支持高效的排序路径搜索,并包含基于接近度和子结果到达时间的查询优化策略。除了作为R2DF数据模型的第一个数据管理系统之外,R2DB还提供了一种基于兴趣特征(FoI)的创新方法,用于可视化大型查询结果集(即数据图的子图)。
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