@proceedings {985,
	title = {DaSeLab at LLMs4OL 2024 Task A: Towards Term Typing in Ontology Learning},
	journal = {The 23rd Internatinal Semantic Web Conference, ISWC 2024},
	volume = {1st LLMs4OL Challenge @ ISWC 2024},
	year = {2024},
	publisher = {TIB Open Access Publishing proceedings},
	address = { Maryland, USA},
	author = {Adrita Barua and Saki Norouzi, Sanaz and Hitzler, Pascal}
}
@article {895,
	title = {{An efficient algorithm for reasoning over OWL EL ontologies with nominal schemas}},
	journal = {Journal of Logic and Computation},
	year = {2022},
	month = {05},
	abstract = {<p>{Nominal schemas have been proposed as an extension to Description Logics (DL), the knowledge representation paradigm underlying the Web Ontology Language (OWL). They provide for a very tight integration of DL and rules. Nominal schemas can be understood as syntactic sugar on top of OWL. However, this naive perspective leads to inefficient reasoning procedures. In order to develop an efficient reasoning procedure for the language \\$\\{\\mathcal \\{E\\}\\mathcal \\{L\\}\\mathcal \\{V\\}^\\{++\\}\\}\\$, which results from extending the OWL profile language OWL EL with nominal schemas, we propose a transformation from \\$\\{\\mathcal \\{E\\}\\mathcal \\{L\\}\\mathcal \\{V\\}^\\{++\\}\\}\\$ ontologies into Datalog-like rule programs that can be used for satisfiability checking and assertion retrieval. The use of this transformation enables the use of powerful Datalog engines to solve reasoning tasks over \\$\\{\\mathcal \\{E\\}\\mathcal \\{L\\}\\mathcal \\{V\\}^\\{++\\}\\}\\$ ontologies. We implement and then evaluate our approach on several real-world, data-intensive ontologies, and find that it can outperform state-of-the-art reasoners such as Konclude and ELK. As a lesser side result we also provide a self-contained description of a rule-based algorithm for \\$\\{\\mathcal \\{E\\}\\mathcal \\{L\\}^\\{++\\}\\}\\$, which does not require a normal form transformation.}</p>
},
	issn = {0955-792X},
	doi = {10.1093/logcom/exac032},
	url = {https://doi.org/10.1093/logcom/exac032},
	author = {Carral, David and Zalewski, Joseph and Hitzler, Pascal}
}
@conference {888,
	title = {Semantic Compression with Region Calculi in Nested Hierarchical Grids},
	booktitle = {Proceedings of the 29th International Conference on Advances in Geographic Information Systems},
	year = {2021},
	pages = {305{\textendash}308},
	publisher = {Association for Computing Machinery},
	organization = {Association for Computing Machinery},
	address = {New York, NY, USA},
	abstract = {<p>We propose the combining of region connection calculi with nested hierarchical grids for representing spatial region data in the context of knowledge graphs, thereby avoiding reliance on vector representations. We present a resulting region calculus, and provide qualitative and formal evidence that this representation can be favorable with large data volumes in the context of knowledge graphs; in particular we study means of efficiently choosing which triples to store to minimize space requirements when data is represented this way, and we provide an algorithm for finding the smallest possible set of triples for this purpose including an asymptotic measure of the size of this set for a special case. We prove that a known constraint calculus is adequate for the reconstruction of all triples describing a region from such a pruned representation, but problematic for reasoning with hierarchical grids in general.</p>
},
	keywords = {Hierarchical Grids, Knowledge Graphs, RCC5},
	isbn = {9781450386647},
	doi = {10.1145/3474717.3483965},
	url = {https://doi.org/10.1145/3474717.3483965},
	author = {Zalewski, Joseph and Hitzler, Pascal and Janowicz, Krzysztof}
}
