An Instance-based Approach for Aligning Resources in the LOD Cloud - Laaziz, Mohamed Najib
36,99 €
inkl. MwSt.
Versandkostenfrei*
Versandfertig in 1-2 Wochen
payback
18 °P sammeln
  • Broschiertes Buch

Linked data has become an essential component in the Semantic Web world. This data is growing into more and more linked instances distributed over different existing ontologies. In this context, there is an important need to improve the interoperability between different ontologies based on term mapping computation. Intensive work has been dedicated to developing very efficient matching algorithms. These methods that rely for instance on graph structures, machine learning, background knowledge, etc. can be considerably improved by the use of the huge amount of links already existing in the…mehr

Andere Kunden interessierten sich auch für
Produktbeschreibung
Linked data has become an essential component in the Semantic Web world. This data is growing into more and more linked instances distributed over different existing ontologies. In this context, there is an important need to improve the interoperability between different ontologies based on term mapping computation. Intensive work has been dedicated to developing very efficient matching algorithms. These methods that rely for instance on graph structures, machine learning, background knowledge, etc. can be considerably improved by the use of the huge amount of links already existing in the Linked Open Data (LOD) cloud. In this book, we will gather data coming from different domains and scattered sources which are related but using different vocabularies making their interoperability very challenging. Most of this data is available as an LOD cloud.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Autorenporträt
Mohamed Najib Laaziz, a graduate of the University of Eastern Finland, is an ambitious web developer with a great interest in the Semantic Web. Linked Data and its optimization have been the center of his research work. Laaziz took over a topic that, although of great relevance, has not had a big share of research among the Semantic Web community.