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Künstliche Intelligenz 30(2) - Juni 2016

https://dl.gi.de/handle/20.500.12116/11099
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Auflistung Künstliche Intelligenz 30(2) - Juni 2016 nach Schlagwort "Ontologies"

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  • Zeitschriftenartikel
    15 Years of Semantic Web: An Incomplete Survey
    (KI - Künstliche Intelligenz: Vol. 30, No. 2, 2016) Glimm, Birte; Stuckenschmidt, Heiner
    It has been 15 years since the first publications proposed the use of ontologies as a basis for defining information semantics on the Web starting what today is known as the Semantic Web Research Community. This work undoubtedly had a significant influence on AI as a field and in particular the knowledge representation and Reasoning Community that quickly identified new challenges and opportunities in using Description Logics in a practical setting. In this survey article, we will try to give an overview of the developments the field has gone through in these 15 years. We will look at three different aspects: the evolution of Semantic Web Language Standards, the evolution of central topics in the Semantic Web Community and the evolution of the research methodology.
  • Zeitschriftenartikel
    Is Your Database System a Semantic Web Reasoner?
    (KI - Künstliche Intelligenz: Vol. 30, No. 2, 2016) Krötzsch, Markus; Rudolph, Sebastian
    Databases and semantic technologies are an excellent match in scenarios requiring the management of heterogeneous or incomplete data. In ontology-based query answering, application knowledge is expressed in ontologies and used for providing better query answers. This enhancement of database technology with logical reasoning remains challenging—performance is critical. Current implementations use time-consuming pre-processing to materialise logical consequences or, alternatively, compute a large number of large queries to be answered by a database management system (DBMS). Recent research has revealed a third option using recursive query languages to “implement” ontological reasoning in DBMS. For lightweight ontology languages, this is possible using the popular Semantic Web query language SPARQL 1.1, other cases require more powerful query languages like Datalog, which is also seeing a renaissance in DBMS today. Herein, we give an overview of these areas with a focus on recent trends and results.