Encoding Semantic Awareness in Resource-Constrained Devices

With the semantic Web relying on ontologies to establish online machine- interpretable information, the Internet is growing into a semantically aware computing paradigm that facilitates Web entities' discovery of the knowledge and resources they need. Ambient intelligence aims to enable smart i...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE intelligent systems Jg. 23; H. 2; S. 26 - 33
Hauptverfasser: Preuveneers, D., Berbers, Y.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Los Alamitos IEEE 01.03.2008
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
algorithms for data and knowledge management
Ambient intelligence
Artificial intelligence
Computation
Computer architecture
Context awareness
Devices
Encoding
Intelligent agents
Intelligent systems
Internet
Large-scale systems
Machine intelligence
On-line systems
Ontologies
Ontology
ontology languages
Pervasive computing
Representations
Semantic Web
Semantics
ISSN:1541-1672, 1941-1294
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:With the semantic Web relying on ontologies to establish online machine- interpretable information, the Internet is growing into a semantically aware computing paradigm that facilitates Web entities' discovery of the knowledge and resources they need. Ambient intelligence aims to enable smart interaction beyond the Internet by embedding intelligence into our environment to unobtrusively support users' daily activities. To accomplish these goals, ontologies and semantic awareness are crucial for better understanding a user's context. While interest in the Semantic Web has spurred the development of large-scale semantic grid architectures, expanding the Semantic Web to the other side of the computing spectrum is a complex undertaking. The techniques and tools that support the semantic Web aren't designed to deal with the resource-constrained devices with which people frequently interact in an ambient-intelligence environment. To counter this disadvantage, we developed a coding scheme for ontologies that embeds semantic awareness in devices with limited memory and processing capabilities, such as sensory nodes and smart phones. This scheme provides a compact representation of an ontology and is enhanced with an efficient and effective semantic-matching algorithm.
Bibliographie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-2
content type line 23
ObjectType-Article-1
ObjectType-Feature-2
ISSN:1541-1672
1941-1294
DOI:10.1109/MIS.2008.25