Magliocca, Francesco (2026) Maximally Cooperative Controlled Query Evaluation for Horn Description Logics. [Tesi di dottorato]
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| Tipologia del documento: | Tesi di dottorato |
|---|---|
| Lingua: | English |
| Titolo: | Maximally Cooperative Controlled Query Evaluation for Horn Description Logics |
| Autori: | Autore Email Magliocca, Francesco franciman12@gmail.com |
| Data: | Giugno 2026 |
| Numero di pagine: | 140 |
| Istituzione: | Università degli Studi di Napoli Federico II |
| Dipartimento: | Matematica e Applicazioni "Renato Caccioppoli" |
| Dottorato: | Matematica e Applicazioni |
| Ciclo di dottorato: | 38 |
| Coordinatore del Corso di dottorato: | nome email Nitsch, Carlo carlo.nitsch@unina.it |
| Tutor: | nome email Sauro, Luigi [non definito] |
| Data: | Giugno 2026 |
| Numero di pagine: | 140 |
| Parole chiave: | Ontologies, Privacy, Description Logics, Knowledge Representation |
| Settori scientifico-disciplinari del MIUR: | Area 01 - Scienze matematiche e informatiche > INF/01 - Informatica Area 01 - Scienze matematiche e informatiche > MAT/01 - Logica matematica |
| Informazioni aggiuntive: | Ciclo 38 |
| Depositato il: | 17 Giu 2026 21:03 |
| Ultima modifica: | 12 Ago 2026 05:37 |
| URI: | https://www.fedoa.unina.it/id/eprint/16030 |
Abstract
Ontology-Mediated Query Answering (OMQA) enables powerful data extraction but introduces confidentiality risks. Controlled Query Evaluation (CQE) is a logic-based approach widely investigated in the literature to develop inference-proof query answerings However, existing CQE approaches to OMQA rely on static censors that fail to provide maximally cooperative answers. To overcome this, this thesis introduces the abstract formalization of Maximally Cooperative Censor-based CQE (MC-CQE) Semantics, providing a dynamic approach to CQE while ensuring robust indistinguishability-based security. The research proposes dynCQE[⪯], a parameterized family of MC-CQE Semantics that leverages preference relations over answer sets to dynamically select optimal, maximally cooperative responses. A comprehensive analysis of the complexity of reasoning under MC-CQE Semantics and the dynCQE[⪯] Semantics is provided for various relevant Horn fragments of the SROIQ Description Logics (Horn SROIQ, Horn SHOIQ, EL and DL-Lite_R) and various fragments of Union of Conjunctive Queries.
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