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Künstliche Intelligenz 30(2) - Juni 2016

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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.
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    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.
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    LOD for Library Science: Benefits of Applying Linked Open Data in the Digital Library Setting
    (KI - Künstliche Intelligenz: Vol. 30, No. 2, 2016) Latif, Atif; Scherp, Ansgar; Tochtermann, Klaus
    Linked Open Data (LOD) has gained widespread adoption by large industries as well as non-profit organizations and governmental organizations. One of the early adopters of LOD technologies are libraries. Since the “early years”, libraries have been key use case and innovation driver for LOD and significantly contributed to the adoption of semantic technologies. The first part of this paper presents selected success stories of current activities in the Linked Data Library community. In a nutshell, these studies include (1) a conceptualization of the Linked Data Value chain, (2) a case study for consumption of Linked Data in a digital journal environment, and (3) an approach to publish metadata on the Semantic Web from an Open Access repository. These stories reveal a strong relationship between LOD in libraries and research topics addressed in traditional fields of computer science such as artificial intelligence, databases, and knowledge discovery. Thus, in the second part of this paper we systematically review the relation of LOD in digital libraries from a computer science perspective. We discuss current LOD research topics such as data integration and schema integration, distributed data management, and others. These challenges have been discussed with computer scientists at a German national database meetup as well as with librarians from ZBW—Leibniz Information Center for Economics and at international librarians meetup.
  • Zeitschriftenartikel
    Semantic Web Reloaded: An Update on the Progress of Semantic Web technologies
    (KI - Künstliche Intelligenz: Vol. 30, No. 2, 2016) Visser, Ubbo
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    Abductive Conjunctive Query Answering w.r.t. Ontologies
    (KI - Künstliche Intelligenz: Vol. 30, No. 2, 2016) Möller, Ralf; Özçep, Özgür; Haarslev, Volker; Nafissi, Anahita; Wessel, Michael
    In this article we investigate abductive conjunctive query answering w.r.t. ontologies and show how use cases can benefit from this kind of query answering service. While practical reasoning systems such as Racer have supported abductive conjunctive query answering for 10 years now, and many projects have exploited this feature, few publications deal with A-box abduction from an implementation perspective. This article gives a generalized overview on features provided by practical systems and also explains optimization techniques needed to meet practical requirements.
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    Semantic Web Service Search: A Brief Survey
    (KI - Künstliche Intelligenz: Vol. 30, No. 2, 2016) Klusch, Matthias; Kapahnke, Patrick; Schulte, Stefan; Lecue, Freddy; Bernstein, Abraham
    Scalable means for the search of relevant web services are essential for the development of intelligent service-based applications in the future Internet. Key idea of semantic web services is to enable such applications to perform a high-precision search and automated composition of services based on formal ontology-based representations of service semantics. In this paper, we briefly survey the state of the art of semantic web service search.
  • Zeitschriftenartikel
    Ontology-Based Multiple Choice Question Generation
    (KI - Künstliche Intelligenz: Vol. 30, No. 2, 2016) Alsubait, Tahani; Parsia, Bijan; Sattler, Ulrike
    Multiple choice questions (MCQs) are considered highly useful (being easy to take or mark) but quite difficult to create and large numbers are needed to form valid exams and associated practice materials. The idea of re-using an existing ontology to generate MCQs almost suggests itself and has been explored in various projects. In this project, we are applying suitable educational theory regarding assessments and related methods for their evaluation to ontology-based MCQ generation. In particular, we investigate whether we can measure the similarity of the concepts in an ontology with sufficient reliability so that this measure can be used to control the difficulty of the MCQs generated. In this report, we provide an overview of the background to this research, and describe the main steps taken and insights gained.
  • Zeitschriftenartikel
    14th International Semantic Web Conference 2015 Bethlehem, PA, USA; October 11–15
    (KI - Künstliche Intelligenz: Vol. 30, No. 2, 2016) Paulheim, Heiko