Description Logics in Multimedia Reasoning

Sikos, Leslie F.

doi:10.1007/978-3-319-54066-5

Cited by 37 publications

(17 citation statements)

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“…The suggested stages for the construction of an ontology from REFSENO in the Conceptual level are: i) Construction, ii) Evolution and iii) Validation. In addition to these stages, for the definition of OntoAgile was also followed the Description Logic -DL for being more expressive than the propositional logic [43].…”

Section: Refseno: a Representation Formalism For Software Engineeringmentioning

confidence: 99%

OntoAgile: an ontology for agile software development processes

Ordoñez¹,

Pardo²,

Pino-Correa³

2019

DYNA

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Currently, there is a broad portfolio of agile approaches to software development, however, in many cases their implementation is done informally and without a proper institutionalization of the agile values and principles. Although there are some proposals related to the adoption and assessment of agile approaches, efforts have been made without having a common terminology which has led to confusion and terminological conflict affecting the implementation of these approaches in organizations. This article proposes the ontology called OntoAgile, which aims to suggest a common and consistent terminology that allows sharing the knowledge generated around the implementation of the agile approaches in the software processes in a generic and formal way. Similarly, OntoAgile facilitates the assessment of the agility of the software processes from the identification of the relationships between the elements of the software processes and the agile principles and values. OntoAgile was assessed satisfactorily by three cases of application.

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Section: Refseno: a Representation Formalism For Software Engineeringmentioning

confidence: 99%

OntoAgile: an ontology for agile software development processes

Ordoñez¹,

Pardo²,

Pino-Correa³

2019

DYNA

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“…RBox axioms Most multimedia ontologies described in the literature correspond to formalisms in which the knowledge base is defined as the combination of a TBox and an ABox (Sikos, 2017b). RBox axioms are supported in very expressive DLs only, such as SROIQ, to collect all statements related to roles and the interdependencies between roles, including a role hierarchy, a finite collection of generalized role assertion axioms of the form R ⊑ S, role equivalence axioms of the form R ≡ S, complex role inclusions of the form Table 4.…”

Section: Abox Axiomsmentioning

confidence: 99%

VidOnt: a core reference ontology for reasoning over video scenes

Sikos

2018

Journal of Information and Telecommunication

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The conceptualization of domains depicted in videos is a necessary, but not sufficient requirement for reasoning-based high-level scene interpretation, which requires the formal representation of the timeline structure, the moving regions of interest, and video production standards, facilities, and procedures as well. Multimedia ontologies, including the very few video ontologies, however, are not exhaustive in terms of concept coverage, redefine terms against Semantic Web best practices, are not aligned with standards, and do not define complex roles and role interdependencies. Because most multimedia ontologies implement only a minimal subset of the mathematical constructors of OWL, and define a TBox and an ABox, but not an RBox, they do not support complex inferencing. This paper describes a formally grounded core reference ontology for video representation, which addresses many of these issues and limitations.

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“…The MPEG-7 descriptors can be used for tasks such as generating video summaries [7] and matching video clips [8], however, they do not convey information about the meaning of audiovisual contents, i.e., they cannot provide high-level semantics [9]. Nevertheless, MPEG-7 terms can be used for low-level descriptors.…”

Section: A Intended Semanticsmentioning

confidence: 99%

“…The four fundamental ontologies that can be employed in video representation, and are imported by several higherlevel video ontologies, are the SWRL Temporal Ontology, 8 the Event Ontology, 9 the Timeline Ontology, 10 and the Multitrack Ontology. 11 There are many common terms that are defined by multiple ontologies (which is discouraged according to Semantic Web best practices [15]), sometimes with a slightly different name.…”

Section: Criteriamentioning

confidence: 99%

Utilizing Multimedia Ontologies in Video Scene Interpretation via Information Fusion and Automated Reasoning

Sikos¹

2017

Proceedings of the 2017 Federated Conference on Computer Science and Information Systems

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Abstract-There is an overwhelming variety of multimedia ontologies used to narrow the semantic gap, many of which are overlapping, not richly axiomatized, do not provide a proper taxonomical structure, and do not define complex correlations between concepts and roles. Moreover, not all ontologies used for image annotation are suitable for video scene representation, due to the lack of rich high-level semantics and spatiotemporal formalisms. This paper presents an approach for combining multimedia ontologies for video scene representation, while taking into account the specificity of the scenes to describe, minimizing the number of ontologies, complying with standards, minimizing reasoning complexity, and whenever possible, maintaining decidability.

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Description Logics in Multimedia Reasoning

Cited by 37 publications

References 0 publications

OntoAgile: an ontology for agile software development processes

OntoAgile: an ontology for agile software development processes

VidOnt: a core reference ontology for reasoning over video scenes

Utilizing Multimedia Ontologies in Video Scene Interpretation via Information Fusion and Automated Reasoning

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