Recursive graph queries are increasingly popular for extracting information from interconnected data found in various domains such as social networks, life sciences, and business analytics. Graph data often come with schema information that describe how nodes and edges are organized. We propose a type inference mechanism that enriches recursive graph queries with relevant structural information contained in a graph schema. We show that this schema information can be useful in order to improve the performance when evaluating acylic recursive graph queries. Furthermore, we prove that the proposed method is sound and complete, ensuring that the semantics of the query is preserved during the schema-enrichment process.

翻译：递归图查询正日益流行，用于从社交网络、生命科学和商业分析等各个领域的互连数据中提取信息。图数据通常包含描述节点和边组织方式的模式信息。我们提出了一种类型推理机制，该机制利用图模式中包含的相关结构信息来丰富递归图查询。我们证明，这些模式信息有助于提高无环递归图查询评估的性能。此外，我们证明所提出的方法是正确且完备的，确保了在模式丰富过程中查询语义保持不变。