Reachability Queries with Label and Substructure Constraints on Knowledge Graphs

TL;DR

This paper introduces two efficient solutions, UIS and INS, for complex reachability queries with label and substructure constraints on knowledge graphs, significantly improving query processing performance.

Contribution

The paper proposes novel algorithms UIS and INS for LSCR queries on KGs, addressing the lack of efficient solutions for such complex queries.

Findings

UIS is suitable for general edge-labeled graphs.

INS is an efficient local-index-based search strategy.

Experimental results show significant efficiency improvements.

Abstract

Since knowledge graphs (KGs) describe and model the relationships between entities and concepts in the real world, reasoning on KGs often correspond to the reachability queries with label and substructure constraints (LSCR). Specially, for a search path p, LSCR queries not only require that the labels of the edges passed by p are in a certain label set, but also claim that a vertex in p could satisfy a certain substructure constraint. LSCR queries is much more complex than the label-constraint reachability (LCR) queries, and there is no efficient solution for LSCR queries on KGs, to the best of our knowledge. Motivated by this, we introduce two solutions for such queries on KGs, UIS and INS. The former can also be utilized for general edge-labeled graphs, and is relatively handy for practical implementation. The latter is an efficient local-index-based informed search strategy. An extensive experimental evaluation, on both synthetic and real KGs, illustrates that our solutions can efficiently process LSCR queries on KGs.