Cardinality Queries over DL-Lite Ontologies
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. Main Track. Pages 1801-1807.
https://doi.org/10.24963/ijcai.2021/248
Keywords
- Knowledge Representation and Reasoning: Computational Complexity of Reasoning
- Knowledge Representation and Reasoning: Description Logics and Ontologies
Abstract
Ontology-mediated query answering (OMQA) employs structured knowledge and automated reasoning in order to facilitate access to incomplete and possibly heterogeneous data. While most research on OMQA adopts (unions of) conjunctive queries as the query language, there has been recent interest in handling queries that involve counting. In this paper, we advance this line of research by investigating cardinality queries (which correspond to Boolean atomic counting queries) coupled with DL-Lite ontologies. Despite its apparent simplicity, we show that such an OMQA setting gives rise to rich and complex behaviour. While we prove that cardinality query answering is tractable (TC0) in data complexity when the ontology is formulated in DL-Lite-core, the problem becomes coNP-hard as soon as role inclusions are allowed. For DL-Lite-pos-H (which allows only positive axioms), we establish a P-coNP dichotomy and pinpoint the TC0 cases; for DL-Lite-core-H (allowing also negative axioms), we identify new sources of coNP complexity and also exhibit L-complete cases. Interestingly, and in contrast to related tractability results, we observe that the canonical model may not give the optimal count value in the tractable cases, which led us to develop an entirely new approach based upon exploring a space of strategies to determine the minimum possible number of query matches.
@inproceedings{ijcai2021p248,
title = {Cardinality Queries over DL-Lite Ontologies},
author = {Bienvenu, Meghyn and Manière, Quentin and Thomazo, Michael},
booktitle = {Proceedings of the Thirtieth International Joint Conference on
Artificial Intelligence, {IJCAI-21}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Prof. Zhi-Hua Zhou},
pages = {1801--1807},
year = {2021},
month = {8},
note = {Main Track},
doi = {10.24963/ijcai.2021/248},
url = {https://doi.org/10.24963/ijcai.2021/248},
}
TY - CPAPER TI - Cardinality Queries over DL-Lite Ontologies AU - Bienvenu, Meghyn AU - Manière, Quentin AU - Thomazo, Michael T2 - Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21 PB - International Joint Conferences on Artificial Intelligence Organization PY - 2021 SP - 1801 EP - 1807 DO - 10.24963/ijcai.2021/248 UR - https://doi.org/10.24963/ijcai.2021/248 ER -Copied
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