March 26, 2022
Conference Paper

QLiG: Query Like a Graph For Subgraph Matching


A graph is a natural and flexible modeling approach to represent entities and relationships between them in real-world. A Knowledge Graphs (KG) is a specialized graph with formal and structured representation of facts, relationships, annotated with semantic descriptions. Subgraph matching is one of the fundamental graph problems to identify relationships, interactions and activities of interest within a large graph. A query specification is a collection of abstract components, operations, and constraints to express a pattern. The specification can be implemented in different ways based on underlying data model. Various graph query specifications have been developed over the years and have led to the development of different open-sourced and vendor-specific query languages. Such specification are modeled as an extension of relational algebra used to develop relational query languages such as SQL. Such relational concepts do not inherently support graph queries. There is a need to represent graph queries in terms on graph-based components to expedite query construction by non-database experts. We present a graph-based query approach QLiG (pronounced cleeg), to perform subgraph matching in Labeled Property Graph. We present the query specifications, salient features, and a use case to show functional examples.

Published: March 26, 2022


Purohit S., P.S. Mackey, J.D. Zucker, A. Bohra, R.D. Deshmukh, and G. Chin. 2021. QLiG: Query Like a Graph For Subgraph Matching. In IEEE Artificial Intelligence & Knowledge Engineering (AIKE 2021), December 1-3, 2021, Laguna Hills, CA, 121-128. Piscataway, New Jersey:IEEE. PNNL-SA-167142. doi:10.1109/AIKE52691.2021.00025

Research topics