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Exploring Reasoning for Utilizing the Full Potential of Semantic Web
Published in Archana Patel, Narayan C. Debnath, Bharat Bhushan, Semantic Web Technologies, 2023
Ayesha Ameen, Khaleel Ur Rahman Khan, B. Padmaja Rani
Description Logic is a formal knowledge representation language [10]. DL is further expressive than propositional logic. The core reasoning problems for DLs are generally decidable and efficient decision techniques are designed for them. DL is tailored to depict knowledge in the domain in a well-understood and organized manner. Artificial intelligence uses DL for describing and performing reasoning about the concepts in the domain. DL is particularly important because they offer logical formalism for ontologies. OWL and its profiles are based on DLs. DL describes the important things in the domain of interest as concepts also called classes, roles also called relations or properties, and individuals and their relationships. Axioms which are logical statements relating to roles and concepts are fundamental modeling concepts in DL. The knowledge base of DL represents terminology (Tbox) and data (Abox) separately. DL architecture is depicted as follows in Figure 6.2.
Building product models, terminologies, and object type libraries
Published in Pieter Pauwels, Kris McGlinn, Buildings and Semantics, 2023
Aaron Costin, Jeffrey W. Ouellette, Jakob Beetz
One such language that incorporates RDF is the Web Ontology Language (OWL) . There are three levels of OWL: OWL Lite, OWL DL (Description Logic), and OWL Full. The simplest level, OWL Lite, supports only a subset of the OWL language constructs, and provides a classification hierarchy and simple constraints. OWL Lite is used by users who want to support OWL full, but want to start at a basic level. In addition to rules and requirements of OWL Lite, OWL DL adds the tools and features of Description Logic to represent the relations between objects and their properties. Description Logic, the basis of any ontology language, is the formal knowledge representation used to express the conceptualisation of domains in an organised and formally well-understood manner. OWL Full provides the highest freedom of using the OWL language and RDF constructs, but takes considerably more computing power to run the inference engines. The current release, OWL 2 (Figure 1.6), can be found in the W3C standards pages.2 Additionally, the Rule Interchange Format (RIF) defines a standard for exchanging rules among systems on the Web that specifies how RDF, RDFS, and OWL interrelate.
Event detection based on open information extraction and ontology
Published in Journal of Information and Telecommunication, 2020
Sihem Sahnoun, Samir Elloumi, Sadok Ben Yahia
The reasoning is a stage after entering the instances and linking them by their specific relations. The reasoner is a software which infers logical consequences from a set of rules to affect for each instance its role (event). Ontology Web Language (OWL) is based on description logics, and it supports automated reasoning. Protégé OWL provides direct access to reasoners such as HERMIT. The later can determine whether or not the ontology is consistent, identify subsumption relationships between classes, to say the least. The tokens that are recognized by named entities, i.e. QNB, Mark and president, will be entered as instances under the classes of the ontology and will be connected by their corresponding relationships, namely, appoint, as. This step is the matching phase who the process is explained by Algorithm 4.
VidOnt: a core reference ontology for reasoning over video scenes*
Published in Journal of Information and Telecommunication, 2018
Using the atomic concepts in compound statements, complex concept expressions can be formed. The description logic supports a wide range of concept expression constructors, including concept assertion, conjunction, disjunction, complement, top concept, bottom concept, role restrictions (existential and universal restrictions), number restrictions (at-least and at-most restrictions), local reflexivity, and nominals, formally C ::= NC | (C ⊓ D) | (C ⊔ D) | ¬C | ⊤ | ⊥ | ∃R.C | ∀R.C | ⩾nR.C | ⩽nR.C | ∃R.Self | {NI}, where C represents concepts, R represents roles, and n is a nonnegative integer.
Algebra for Enterprise Ontology: towards analysis and synthesis of enterprise models
Published in Enterprise Information Systems, 2018
Description Logics (DL) is a formal language for representing knowledge. It is more powerful than propositional logic or even first-order predicate logic in terms of its expressiveness and decidability in a reasoning problem. Despite its expressiveness, DL has very few previous studies regarding operations on models.