Goal-Driven Query Answering for Existential Rules With Equality


  • Michael Benedikt Oxford University
  • Boris Motik Oxford University
  • Efthymia Tsamoura Alan Turing Institute, Oxford University


reasoning, query answering


Inspired by the magic sets for Datalog, we present a novel goal-driven approach for answering queries over terminating existential rules with equality (aka TGDs and EGDs). Our technique improves the performance of query answering by pruning the consequences that are not relevant for the query. This is challenging in our setting because equalities can potentially affect all predicates in a dataset. We address this problem by combining the existing singularization technique with two new ingredients: an algorithm for identifying the rules relevant to a query and a new magic sets algorithm. We show empirically that our technique can significantly improve the performance of query answering, and that it can mean the difference between answering a query in a few seconds or not being able to process the query at all.




How to Cite

Benedikt, M., Motik, B., & Tsamoura, E. (2018). Goal-Driven Query Answering for Existential Rules With Equality. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/11563



AAAI Technical Track: Knowledge Representation and Reasoning