SPARQLing Datalog for Rule-Based Reasoning over Large Knowledge Graphs
From International Center for Computational Logic
SPARQLing Datalog for Rule-Based Reasoning over Large Knowledge Graphs
Talk by Alex Ivliev
- Location: APB-2026
- Start: 6. August 2026 at 11:00 am
- End: 6. August 2026 at 12:00 pm
- Research group: Knowledge-Based Systems
- Event series: Research Seminar Logic and AI
- iCal
The talk will propose a new integration of rule reasoners with one or more RDF stores, using selective SPARQL queries to fetch relevant data. In contrast to previous implementations that merely import results of fixed SPARQL queries, the proposed approach relies on pure logic programs over RDF triple data. Transparent to the user, optimised SPARQL queries then are constructed and evaluated during reasoning. To ensure good performance, the approach develops optimisation methods that adopt ideas from logic program optimisation, including semi-naive evaluation, magic sets, and static filtering. Based on the integration of the methods into the open source rule engine Nemo, the talk will empirically evaluate the approach with complex rule sets over large knowledge graphs.
The talk has been presented at ESWC 2026.
