S2CTrans：构建从 SPARQL 到 Cypher 的桥梁
S2CTrans: Building a bridge from SPARQL to Cypher
AI总结：
本文提出了 S2CTrans 框架，基于图关系代数实现了从 SPARQL 到 Cypher 的翻译，在保持语义一致性的同时，有效提升了使用 SPARQL 查询属性图数据库的互操作性与效率。
摘要：
在图数据应用中，数据主要使用两种模型进行维护：RDF（Resource Description Framework）和属性图。属性图模型被工业界广泛采用，使得属性图数据库在图遍历查询性能上通常优于 RDF 数据库。然而，用户通常更喜欢使用 SPARQL 作为查询语言，因为它是 W3C 的推荐标准。因此，探索 SPARQL 到属性图查询语言的翻译对于增强图查询语言的互操作性，并使用 SPARQL 对属性图进行有效查询至关重要。尽管 SPARQL 与 Cypher 等属性图查询语言在语义表示和处理逻辑上存在巨大差异，本文展示了使用图关系代数将 SPARQL 翻译为 Cypher 以进行图遍历查询的可行性。我们提出了 S2CTrans 框架，该框架实现了 SPARQL 到 Cypher 的翻译，同时保留了原始语义。使用 Berlin SPARQL Benchmark (BSBM) 数据集的实验结果表明，S2CTrans 成功将 SPARQL 1.1 规范中的大多数 SELECT 查询转换为类型安全的 Cypher 语句，保持了结果一致性，并提高了使用 SPARQL 进行数据查询的效率。
英文摘要：
In graph data applications, data is primarily maintained using two models: RDF (Resource Description Framework) and property graph. The property graph model is widely adopted by industry, leading to property graph databases generally outperforming RDF databases in graph traversal query performance. However, users often prefer SPARQL as their query language, as it is the W3C's recommended standard. Consequently, exploring SPARQL-to-Property-Graph-Query-Language translation is crucial for enhancing graph query language interoperability and enabling effective querying of property graphs using SPARQL. Despite the substantial differences in semantic representation and processing logic between SPARQL and property graph query languages like Cypher, this paper demonstrates the feasibility of translating SPARQL to Cypher for graph traversal queries using graph relational algebra. We present the S2CTrans framework, which achieves SPARQL-to-Cypher translation while preserving the original semantics. Experimental results with the Berlin SPARQL Benchmark (BSBM) datasets show that S2CTrans successfully converts most SELECT queries in the SPARQL 1.1 specification into type-safe Cypher statements, maintaining result consistency and improving the efficiency of data querying using SPARQL.
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。
