Query Answering for Existential Rules via Efficient Datalog Rewriting

Query Answering for Existential Rules via Efficient Datalog Rewriting

Zhe Wang, Peng Xiao, Kewen Wang, Zhiqiang Zhuang, Hai Wan

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
Main track. Pages 1933-1939. https://doi.org/10.24963/ijcai.2020/268

Existential rules are an expressive ontology formalism for ontology-mediated query answering and thus query answering is of high complexity, while several tractable fragments have been identified. Existing systems based on first-order rewriting methods can lead to queries too large for DBMS to handle. It is shown that datalog rewriting can result in more compact queries, yet previously proposed datalog rewriting methods are mostly inefficient for implementation. In this paper, we fill the gap by proposing an efficient datalog rewriting approach for answering conjunctive queries over existential rules, and identify and combine existing fragments of existential rules for which our rewriting method terminates. We implemented a prototype system Drewer, and experiments show that it is able to handle a wide range of benchmarks in the literature. Moreover, Drewer shows superior or comparable performance over state-of-the-art systems on both the compactness of rewriting and the efficiency of query answering.
Keywords:
Knowledge Representation and Reasoning: Description Logics and Ontologies