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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 Titel

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  • Zeitschriftenartikel
    14th International Semantic Web Conference 2015 Bethlehem, PA, USA; October 11–15
    (KI - Künstliche Intelligenz: Vol. 30, No. 2, 2016) Paulheim, Heiko
  • 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
    A System for Probabilistic Linking of Thesauri and Classification Systems
    (KI - Künstliche Intelligenz: Vol. 30, No. 2, 2016) Posch, Lisa; Schaer, Philipp; Bleier, Arnim; Strohmaier, Markus
    This paper presents a system which creates and visualizes probabilistic semantic links between concepts in a thesaurus and classes in a classification system. For creating the links, we build on the Polylingual Labeled Topic Model (PLL-TM) (Posch et al., in KI 2015: advances in artificial intelligence, 2015). PLL-TM identifies probable thesaurus descriptors for each class in the classification system by using information from the natural language text of documents, their assigned thesaurus descriptors and their designated classes. The links are then presented to users of the system in an interactive visualization, providing them with an automatically generated overview of the relations between the thesaurus and the classification system.
  • Zeitschriftenartikel
    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.
  • Zeitschriftenartikel
    Applying Linked Data Technologies in the Social Sciences
    (KI - Künstliche Intelligenz: Vol. 30, No. 2, 2016) Zapilko, Benjamin; Schaible, Johann; Wandhöfer, Timo; Mutschke, Peter
    In recent years, Linked Open Data (LOD) has matured and gained acceptance across various communities and domains. Large potential of Linked Data technologies is seen for an application in scientific disciplines. In this article, we present use cases and applications for an application of Linked Data in the social sciences. They focus on (a) interlinking domain-specific information, and (b) linking social science data to external LOD sources (e.g. authority data) from other domains. However, several technical and research challenges arise, when applying Linked Data technologies to a scientific domain with its specific data, information needs and use cases. We discuss these challenges and show how they can be addressed.
  • Zeitschriftenartikel
    Extracting Semantics from Unconstrained Navigation on Wikipedia
    (KI - Künstliche Intelligenz: Vol. 30, No. 2, 2016) Niebler, Thomas; Schlör, Daniel; Becker, Martin; Hotho, Andreas
    Semantic relatedness between words has been successfully extracted from navigation on Wikipedia pages. However, the navigational data used in the corresponding works are sparse and expected to be biased since they have been collected in the context of games. In this paper, we raise this limitation and explore if semantic relatedness can also be extracted from unconstrained navigation. To this end, we first highlight structural differences between unconstrained navigation and game data. Then, we adapt a state of the art approach to extract semantic relatedness on Wikipedia paths. We apply this approach to transitions derived from two unconstrained navigation datasets as well as transitions from WikiGame and compare the results based on two common gold standards. We confirm expected structural differences when comparing unconstrained navigation with the paths collected by WikiGame. In line with this result, the mentioned state of the art approach for semantic extraction on navigation data does not yield good results for unconstrained navigation. Yet, we are able to derive a relatedness measure that performs well on both unconstrained navigation data as well as game data. Overall, we show that unconstrained navigation data on Wikipedia is suited for extracting semantics.
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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.
  • Zeitschriftenartikel
    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.