The property graph is an increasingly popular data model. Pattern construction and pattern matching are important tasks when dealing with property graphs. Given a property graph schema S, a property graph G, and a query pattern P, all expressed in language L, pattern matching is the process of finding, merging, and annotating subgraphs of G that match P. Expressive pattern languages support topological constraints, property values constraints, negations, quantifications, aggregations, and path semantics. Calculated properties may be defined for vertices, edges, and subgraphs, and constraints may be imposed on their evaluation result. Query posers would like to construct patterns with minimal effort, minimal trial and error, and in a manner that is coherent with the way they think. The ability to express patterns in a way that is aligned with their mental processes is crucial to the flow of their work and to the quality of the insights they can draw. Since the capabilities of the human visual system with respect to pattern perception are remarkable, it is a matter of course that query patterns were to be expressed visually. Visual query languages have the potential to be much more 'user-friendly' than their textual counterparts in the sense that patterns may be constructed and understood much more quickly and with much less mental effort. A long-standing challenge is to design a visual query language that is generic, has rich expressive power, and is highly receptive and productive. V1 attempts to answer this challenge. V1 is a declarative visual pattern query language for schema-based property graphs. V1 supports property graphs with mixed (both directed and undirected) edges and unary edges, with multivalued and composite properties, and with null property values. V1 is generic, concise, has rich expressive power, and is highly receptive and productive.
翻译:属性图是一个越来越受欢迎的数据模型。 在处理属性图时, 模式构建和模式匹配是重要的任务。 在使用属性图 S 、 属性图 G 和 查询图 P 时, 以语言L 表示, 模式匹配是查找、 合并和注解符合 P. 表示模式语言的 G 子集的过程, 支持地形限制、 财产价值限制、 否定、 量化、 聚合和路径语义。 计算属性可能是用于处理属性图案、 边缘 和子图案的重要任务, 可能对其评价结果施加限制。 询问图案显示的图案模式以最小努力、 最小尝试和错误的方式构建模式, 并且与他们的想法一致的 G. 表达模式的能力对于其工作的流量、 属性限制、 否定、 量化、 汇总和路径描述质量来说至关重要。 由于人类视觉系统对模式认知的精确度是惊人的, 直态和子图案支持直线图的表达方式。 视觉查询语言具有快速的直观和直径, 其直观的图案的图解和直观的图案的图案力和直观的图案的图案的图案力和直径更接近, 和直观的图案的图案的图案的图, 和直达理解的图案的图案的图案的图案的图案的图案的图案, 和直达的图案的图案的图案可以理解和直到的图, 和直到的图案的图案的图, 和直路, 和直达的图, 和直通的图的图和直通的图案的图案的图案的图案的图案的图案的图案的图案力可能理解性力和直达的判的判的判的图, 和直到的图, 和直到比的图, 和直通的判的图的图和直到的图和直到的推的图, 和直到的图解的图和直到比的图的图和直到比的判的判的判的判的图和直到的图和直到比的图和直到的判的判的判的判的图和直到的图和直到的判