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Description Logics (DLs) are suitable, well-known, logics for managing structured knowledge. They allow reasoning about individuals and well defined concepts, i.e., set of individuals with common properties. The experience in using DLs in…

Artificial Intelligence · Computer Science 2011-06-06 U. Straccia

A prominent problem in knowledge representation is how to answer queries taking into account also the implicit consequences of an ontology representing domain knowledge. While this problem has been widely studied within the realm of…

Artificial Intelligence · Computer Science 2021-11-24 Gabriella Pasi , Rafael Peñaloza

Fuzzy Description Logics (FDLs) are logic-based formalisms used to represent and reason with vague or imprecise knowledge. It has been recently shown that reasoning in most FDLs using truth values from the interval [0,1] becomes undecidable…

Artificial Intelligence · Computer Science 2015-09-30 Stefan Borgwardt , Rafael Peñaloza

It is widely recognized today that the management of imprecision and vagueness will yield more intelligent and realistic knowledge-based applications. Description Logics (DLs) are a family of knowledge representation languages that have…

Artificial Intelligence · Computer Science 2011-11-02 I. Horrocks , J. Z. Pan , G. Stamou , G. Stoilos , V. Tzouvaras

Conjunctive queries play an important role as an expressive query language for Description Logics (DLs). Although modern DLs usually provide for transitive roles, conjunctive query answering over DL knowledge bases is only poorly understood…

Artificial Intelligence · Computer Science 2011-11-02 Birte Glimm , Ian Horrocks , Carsten Lutz , Ulrike Sattler

Description Logics (DLs) are appropriate, widely used, logics for managing structured knowledge. They allow reasoning about individuals and concepts, i.e. set of individuals with common properties. Typically, DLs are limited to dealing with…

Artificial Intelligence · Computer Science 2016-11-17 Haibin Wang , Andre Rogatko , Florentin Smarandache , Rajshekhar Sunderraman

Querying large datasets with incomplete and vague data is still a challenge. Ontology-based query answering extends standard database query answering by background knowledge from an ontology to augment incomplete data. We focus on…

Logic in Computer Science · Computer Science 2018-08-07 Rafael Peñaloza , Veronika Thost , Anni-Yasmin Turhan

Description logics (DLs) are a suitable formalism for representing knowledge about domains in which objects are described not only by attributes but also by binary relations between objects. Fuzzy extensions of DLs can be used for such…

Logic in Computer Science · Computer Science 2020-08-10 Linh Anh Nguyen , Quang-Thuy Ha , Ngoc Thanh Nguyen , Thi Hong Khanh Nguyen , Thanh-Luong Tran

Circumscription is one of the main approaches for defining non-monotonic description logics (DLs). While the decidability and complexity of traditional reasoning tasks such as satisfiability of circumscribed DL knowledge bases (KBs) is well…

Artificial Intelligence · Computer Science 2023-06-08 Carsten Lutz , Quentin Manière , Robin Nolte

In ontology-mediated querying, description logic (DL) ontologies are used to enrich incomplete data with domain knowledge which results in more complete answers to queries. However, the evaluation of ontology-mediated queries (OMQs) over…

Databases · Computer Science 2020-07-30 Pablo Barcelo , Cristina Feier , Carsten Lutz , Andreas Pieris

Large Language Models (LLMs) achieve strong performance in analyzing and generating text, yet they struggle with explicit, transparent, and verifiable reasoning over complex texts such as those containing debates. In particular, they lack…

Artificial Intelligence · Computer Science 2026-03-04 Gianvincenzo Alfano , Sergio Greco , Lucio La Cava , Stefano Francesco Monea , Irina Trubitsyna

Regression problems have been more and more embraced by deep learning (DL) techniques. The increasing number of papers recently published in this domain, including surveys and reviews, shows that deep regression has captured the attention…

Machine Learning · Computer Science 2022-09-12 Jorge S. S. Júnior , Jérôme Mendes , Francisco Souza , Cristiano Premebida

The problem of minimizing finite fuzzy interpretations in fuzzy description logics (FDLs) is worth studying. For example, the structure of a fuzzy/weighted social network can be treated as a fuzzy interpretation in FDLs, where actors are…

Artificial Intelligence · Computer Science 2023-03-22 Linh Anh Nguyen

Ontologies play a central role in structuring knowledge across domains, supporting tasks such as reasoning, data integration, and semantic search. However, their large size and complexity, particularly in fields such as biomedicine,…

Human-Computer Interaction · Computer Science 2025-08-19 Vladimir Zhurov , John Kausch , Kamran Sedig , Mostafa Milani

How can non-classical logic contribute to the analysis of complexity in computer science? In this paper, we give a step towards this question, taking a logical model-theoretic approach to the analysis of complexity in fuzzy constraint…

Logic · Mathematics 2019-11-18 Pilar Dellunde , Amanda Vidal

Aiming to harmonise finite and infinite model reasoning, we initiate the study of partially finite models, where the reasoning task comes with a formula that specifies a part of the model that must be finite. We focus on the problem of…

Logic in Computer Science · Computer Science 2026-04-29 Tomasz Gogacz , Filip Murlak , Marcin Przybyłko , Alexandra Rogova , Michał Skrzypczak

The problem of minimizing fuzzy interpretations in fuzzy description logics (FDLs) is important both theoretically and practically. For instance, fuzzy or weighted social networks can be modeled as fuzzy interpretations, where individuals…

Data Structures and Algorithms · Computer Science 2026-02-05 Linh Anh Nguyen

The paper investigates the properties of a fuzzy logic of typicality. The extension of fuzzy logic with a typicality operator was proposed in recent work to define a fuzzy multipreference semantics for Multilayer Perceptrons, by regarding…

Artificial Intelligence · Computer Science 2021-07-15 Laura Giordano

Ontologies often require knowledge representation on multiple levels of abstraction, but description logics (DLs) are not well-equipped for supporting this. We propose an extension of DLs in which abstraction levels are first-class citizens…

Artificial Intelligence · Computer Science 2023-10-23 Carsten Lutz , Lukas Schulze

Fuzzy Description Logics (DLs) are a family of logics which allow the representation of (and the reasoning with) structured knowledge affected by vagueness. Although most of the not very expressive crisp DLs, such as ALC, enjoy the Finite…

Artificial Intelligence · Computer Science 2010-03-09 Fernando Bobillo , Felix Bou , Umberto Straccia
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