Spectra of Cardinality Queries over Description Logic Knowledge Bases

Abstract

Recent works have explored the use of counting queries coupled with Description Logic ontologies. The answer to such a query in a model of a knowledge base is either an integer or infinity, and its spectrum is the set of its answers over all models. While it is unclear how to compute and manipulate such a set in general, we identify a class of counting queries whose spectra can be effectively represented. Focusing on atomic counting queries, we pinpoint the possible shapes of a spectrum over ALCIF ontologies: they are essentially the subsets of N and infinity closed under addition. For most sublogics of ALCIF, we show that possible spectra enjoy simpler shapes, being [ m, infinity ] or variations thereof. To obtain our results, we refine constructions used for finite model reasoning and notably rely on a cycle-reversion technique for the Horn fragment of ALCIF. We also study the data complexity of computing the proposed effective representation and establish the FP^NP[log]-completeness of this task under several settings.

Cite

Text

Manière and Przybylko. "Spectra of Cardinality Queries over Description Logic Knowledge Bases." AAAI Conference on Artificial Intelligence, 2025. doi:10.1609/AAAI.V39I14.33652

Markdown

[Manière and Przybylko. "Spectra of Cardinality Queries over Description Logic Knowledge Bases." AAAI Conference on Artificial Intelligence, 2025.](https://mlanthology.org/aaai/2025/maniere2025aaai-spectra/) doi:10.1609/AAAI.V39I14.33652

BibTeX

@inproceedings{maniere2025aaai-spectra,
  title     = {{Spectra of Cardinality Queries over Description Logic Knowledge Bases}},
  author    = {Manière, Quentin and Przybylko, Marcin},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2025},
  pages     = {15067-15074},
  doi       = {10.1609/AAAI.V39I14.33652},
  url       = {https://mlanthology.org/aaai/2025/maniere2025aaai-spectra/}
}