Multi-viewpoint Ontological Representation of Composite Concepts : a Description Logics Based Approach

Hemam, Mounir; Djezzar, Meriem; Boufaïda, Zizette

doi:10.1504/ijiids.2016.10002330

“…For instance, in [1] and [21], the context corresponds to time and location where decisions on activities are based on the time and location of the captured data. In [12,25], the context corresponds to a point of view interested in a subset of object properties. However, some properties of an object are assumed to be consensual i.e.…”

Section: Context Awarenessmentioning

confidence: 99%

An Ontology – based Contextual Approach for Cross-domain Applications in Internet of Things

Benkhaled

¹

,

Hemam

²

,

Djezzar

³

et al. 2022

IJCAI

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The Internet of Things is an ecosystem which enables objects and devices, such as sensors or actuators, to communicate and exchange information with each other without human intervention. One of the main challenges in the Internet of Things is the lack of semantic interoperability. Devices cannot understand the meaning of raw data, due to the diversity and heterogeneity in data formats from different sources. In order to deal with semantic interoperability, ontologies are the one way to integrate semantics to raw data. They describe an IoT system and represent the data in a standardized way. The IoT devices provide a great deal of IoT data, mainly used for specific IoT applications such as smart home, smart farming, smart cities or healthcare. Therefore, existing applications became isolated in vertical silos, each one of them use independently their own model (i.e. ontology), which makes this ontologies also limited to a specific domain. Our approach has the goal of breaking down these vertical silos and achieves a semantic interoperability across IoT domains in cross-domain applications. In this paper, we propose a development of a single cross-domain ontology named CDOnto. The latter is considered to be a generic across different IoT domains, which can be extended by domain-specific ontologies. The proposed ontological model follows a contextual approach to organize and distinguish the combined domains (i.e. contexts) representations. In addition, the ontology allows reasoning across overlapping IoT domains and infers a complementary and new knowledge required in cross-domain applications. Povzetek: Predlagamo semantični ontološki model za doseganje semantične interoperabilnosti v kontekstu interneta stvari (IoT).

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“…Several work are interested in the notion of the viewpoint. The authors in [5], [7], [8], [9], [10] and [11] have integrated the viewpoint in the development of the ontology. This ontology called 'multi-viewpoints ontology'.…”

Section: Related Workmentioning

confidence: 99%

Advances in Machine Learning, Data Mining and Computing

2021

0

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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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Introducing the Viewpoint in the Resource Description using Machine Learning

Djama¹

2021

Advances in Machine Learning, Data Mining and Computing

0

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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.

show abstract

Multi-viewpoint Ontological Representation of Composite Concepts : a Description Logics Based Approach

Cited by 3 publications

References 19 publications

An Ontology – based Contextual Approach for Cross-domain Applications in Internet of Things

An Ontology – based Contextual Approach for Cross-domain Applications in Internet of Things

Advances in Machine Learning, Data Mining and Computing

Introducing the Viewpoint in the Resource Description using Machine Learning

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