Graphs are commonly used for representing complex structures such as social relationships, biological interactions, and knowledge bases. In many scenarios, graphs not only represent topological relationships but also store the attributes that denote the semantics associated with their vertices and edges, known as attributed graphs. Attributed graphs can meet demands for a wide range of applications, and thus a variety of queries on attributed graphs have been proposed. However, these diverse types of attributed graph queries have not been systematically investigated yet. In this paper, we provide an extensive survey of several typical types of attributed graph queries. We propose a taxonomy of attributed graph queries based on query inputs and outputs. We summarize the definitions of queries that fall into each category and present a fine-grained classification of queries within each category by analyzing the semantics and algorithmic motivations behind these queries. Moreover, we discuss the insights of how existing studies address the technical challenges of query processing and outline several promising future research directions.

图形通常用于表示复杂的结构，例如社会关系，生物相互作用和知识库。在许多情况下，图不仅表示拓扑关系，而且还存储表示与它们的顶点和边相关联的语义的属性，称为属性图。属性图可以满足广泛应用的需求，因此提出了对属性图的各种查询。但是，尚未对这些不同类型的属性图查询进行系统的研究。在本文中，我们对归因图查询的几种典型类型进行了广泛的调查。我们提出了基于查询输入和输出的属性图查询分类法。我们总结了属于每个类别的查询的定义，并通过分析这些查询背后的语义和算法动机，对每个类别内的查询进行了细粒度分类。此外，我们讨论了现有研究如何解决查询处理技术挑战的见解，并概述了一些有前途的未来研究方向。