An extension of the ontology web language with multi-viewpoints and probabilistic reasoning

Hemam, Mounir

doi:10.1504/ijaip.2018.090789

Cited by 12 publications

(10 citation statements)

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“…Hemam et al [33] have developed a method that allows coupling the notion of the viewpoint and the notion of the composite concepts in the ontology. Then, Hemam in [34] has introduced the probabilistic reasoning in this method.…”

Section: B Related Workmentioning

confidence: 99%

VP-RDF: An RDF Based Framework to Introduce the Viewpoint in the Description of Resources

Djama

2021

Applied Computer Systems

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The description of resources and their relationships is an essential task on the web. Generally, the web users do not share the same interests and viewpoints. Each user wants that the web provides data and information according to their interests and specialty. The existing query languages, which allow querying data on the web, cannot take into consideration the viewpoint of the user. We propose introducing the viewpoint in the description of the resources. The Resource Description Framework (RDF) represents a common framework to share data and describe resources. In this study, we aim at introducing the notion of the viewpoint in the RDF. Therefore, we propose a View-Point Resource Description Framework (VP-RDF) as an extension of RDF by adding new elements. The existing query languages (e.g., SPARQL) can query the VP-RDF graphs and provide the user with data and information according to their interests and specialty. Therefore, VP-RDF can be useful in intelligent systems on the web.

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Section: B Related Workmentioning

confidence: 99%

VP-RDF: An RDF Based Framework to Introduce the Viewpoint in the Description of Resources

Djama

2021

Applied Computer Systems

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“…The multi-viewpoints ontology [8] allows representing domain knowledge in two levels: Consensual and Heterogeneous level.…”

Section: Instantiated Multi-viewpoints Ontologymentioning

confidence: 99%

Introducing the Viewpoint in the Resource Description using Machine Learning

Djama¹

2021

Advances in Machine Learning, Data Mining and Computing

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Search engines allow providing the user with data and information according to their interests and specialty. Thus, it is necessary to exploit descriptions of the resources, which take into consideration viewpoints. Generally, the resource descriptions are available in RDF (e.g., DBPedia of Wikipedia content). However, these descriptions do not take into consideration viewpoints. In this paper, we propose a new approach, which allows converting a classic RDF resource description to a resource description that takes into consideration viewpoints. To detect viewpoints in the document, a machine learning technique will be exploited on an instanced ontology. This latter allows representing the viewpoint in a given domain. An experimental study shows that the conversion of the classic RDF resource description to a resource description that takes into consideration viewpoints, allows giving very relevant responses to the user’s requests.

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“…Hemam et al [18] and Hemam [1] investigated the problem of representing a domain ontology which takes into account the notion of a viewpoint. This type of ontology, which they call a Multi-Viewpoints Ontology (MvpOnt), is a multiple description of a single universe of discourse according to various viewpoints.…”

Section: Multi-viewpoints Ontologymentioning

confidence: 99%

“…Moreover, multi-ontologies allow only the construction of heterogeneous annotations, without a consensual annotation, so that it is necessary to reason about the alignment of disjoint ontologies. So, to accomplish our goals, we exploit the multiviewpoint ontology developed in [1]. A multi-viewpoints ontology is cohabited by heterogeneity at the local level and consensus at the global level.…”

Section: Introductionmentioning

confidence: 99%

“…What is unique in our approach is that one element in a resource can be annotated with different specific concepts, based on different viewpoints. Our approach utilizes a multi-viewpoints ontology [1], with heterogeneity at the local level and consensus at the global level. Povzetek: Predstavljena je metoda za generiranje heterogenih semantičnih anotacij XML strani na osnovi različnih, a skladnih pogledov…”

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confidence: 99%

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Generation of Heterogeneous Semantic Annotations of XML Pages: A Multi-viewpoints Approach

Djezzar¹,

Hemam

Ouhiba

et al. 2021

IJCAI

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The semantic annotations presented in current research are based on consensual descriptions of domain knowledge which are used to generate a consensual interpretation of the resource content. Sometimes specialists in a domain want to enrich this interpretation with specific interpretations based on their specialties, consistent with the interpretations of other specialists. However, extant work cannot enrich consensual annotations with heterogeneous annotations. We propose an approach that constructs a consensual (global) annotation and then enriches the consensual annotation with heterogeneous (local) annotations, each of which is a specification of the global annotation. The heterogeneous annotations are consistent with the global interpretations and with one another. What is unique in our approach is that one element in a resource can be annotated with different specific concepts, based on different viewpoints. Our approach utilizes a multi-viewpoints ontology [1], with heterogeneity at the local level and consensus at the global level. Povzetek: Predstavljena je metoda za generiranje heterogenih semantičnih anotacij XML strani na osnovi različnih, a skladnih pogledov

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An extension of the ontology web language with multi-viewpoints and probabilistic reasoning

Cited by 12 publications

References 0 publications

VP-RDF: An RDF Based Framework to Introduce the Viewpoint in the Description of Resources

VP-RDF: An RDF Based Framework to Introduce the Viewpoint in the Description of Resources

Introducing the Viewpoint in the Resource Description using Machine Learning

Generation of Heterogeneous Semantic Annotations of XML Pages: A Multi-viewpoints Approach

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