Now showing items 184-203 of 307

  • Process Mediation Based on Triple Space Computing 

    Zhou, ZhangBing; Sapkota, Brahmananda; Cimpian, Emilia; Foxvog, Doug; Vasiliu, Laurentiu; Hauswirth, Manfred (Springer, 2008)
    Web services are inherently heterogeneous at both data and behavioral levels because of the nature of the Web, which is the main obstacle to the usability of Web services. The heterogeneity at a behavioral level is generally ...
  • Processing ontology alignments with SPARQL 

    Polleres, Axel (IEEE Computer Society, 2008)
  • Processing ontology alignments with SPARQL 

    Polleres, Axel (IEEE, 2008)
    Solving problems raised by heterogeneous ontologies can be achieved by matching the ontologies and processing the resulting alignments. This is typical of data mediation in which the data must be translated from one ...
  • Produce and Consume Linked Data with Drupal! 

    Corlosquet, Stéphane; Delbru, Renaud; Polleres, Axel; Decker, Stefan (Springer, 2009)
    Currently a large number of Web sites are driven by Content Management Systems (CMS) which manage textual and multimedia content but also - inherently - carry valuable information about a site¿s structure and content ...
  • Protect Your RDF Data! 

    Kirrane, Sabrina; Lopes, Nuno; Mileo, Alessandra; Decker, Stefan (2012)
    The explosion of digital content and the heterogeneity of enterprise content sources have pushed existing data integration solutions to their boundaries. Although RDF can be used as a representation format for integrated data, ...
  • A Protégé Plug-in Development to Support the NEPOMUK Representational Language 

    Caires, Milena; Scerri, Simon; Handschuh, Siegfried (2007)
    In this document, we present the challenges faced to develop a plug-in for Protégé that supports requirements for the NEPOMUK1 Representational Language (NRL). NRL is a language built on top of RDF/S and ...
  • A Prototype to Explore Content and Context on Social Community Sites 

    Bojars, Uldis; Heitmann, Benjamin; Oren, Eyal (2007)
    The SIOC Ontology can be used to express information from the online community sites in a machine readable form using RDF. This rich data structure allows us to easily analyse and extract social relations from these ...
  • Quality-driven resource-adaptive data stream mining? 

    Karnstedt, Marcel (IEEE / ACM, 2011-01)
    Data streams have become ubiquitous in recent years and are handled on a variety of platforms, ranging from dedicated high-end servers to battery-powered mobile sensors. Data stream processing is therefore required to work ...
  • Quantified equilibrium logic and hybrid rules 

    Polleres, Axel (Springer, 2007)
    In the ongoing discussion about combining rules and Ontologies on the Semantic Web a recurring issue is how to combine first-order classical logic with nonmonotonic rule languages. Whereas several modular approaches to de- ...
  • Querying over Federated SPARQL Endpoints - A State of the Art Survey 

    Rakhmawati, Nur; Umbrich, Jürgen; Karnstedt, Marcel; Hasnain, Ali; Hausenblas, Michael (2013)
    The increasing amount of Linked Data and its inherent distributed nature have attracted significant attention throughout the research community and amongst practitioners to search data, in the past years. Inspired by ...
  • Querying Phenotype-Genotype Associations across Multiple Knowledge Bases using Semantic Web Technologies 

    Iqbal, Aftab (2013)
    Biomedical and genomic data are inherently heterogeneous and their recent proliferation over the Web has demanded innovative querying methods to help domain experts in their clinical and research studies. In this paper we ...
  • Random Indexing Explained with High Probability 

    QasemiZadeh, Behrang (2015)
    Random indexing (RI) is an incremental method for constructing a vector space model (VSM) with a reduced dimensionality. Previously, the method has been justified using the mathematical framework of Kanerva's sparse ...
  • Random Manhattan Indexing 

    QasemiZadeh, Behrang; Handschuh, Siegfried (2014)
    Vector space models (VSMs) are mathematically well-defined frameworks that have been widely used in text processing. In these models, high-dimensional, often sparse vectors represent text units. In an application, the ...
  • Random Manhattan Integer Indexing: Incremental L1 Normed Vector Space Construction 

    QasemiZadeh, Behrang; Handschuh, Siegfried (2014)
    Vector space models (VSMs) are mathematically well-defined frameworks that have been widely used in the distributional approaches to semantics. In VSMs, high-dimensional vectors represent linguistic entities. In an ...
  • Rapid Competence Development in Serious Games Using Case-Based Reasoning and Threshold Concepts 

    Hulpus, Ioana; Fradinho, Manuel; Hayes, Conor (2010)
    A major challenge in todays fast pace world is the acquisition of competence in a timely and efficient manner, whilst keeping the individual highly motivated. This paper presents a novel based on the use of serious games ...
  • RDFS & OWL Reasoning for Linked Data 

    Hogan, Aidan; Delbru, Renaud; Umbrich, Jurgen (na, 2013)
    Linked Data promises that a large portion of Web Data will be usable as one big interlinked RDF database against which structured queries can be answered. In this lecture we will show how reasoning - using RDF Schema (RDFS) ...
  • ReConRank: A Scalable Ranking Method for Semantic Web Data with Context 

    Hogan, Aidan; Harth, Andreas; Decker, Stefan (2006)
    We present an approach that adapts the well-known PageRank/HITS algorithms to Semantic Web data. Our method combines ranks from the RDF graph with ranks from the context graph, i.e. data sources and their linkage. We present ...
  • Reconstruction of Threaded Conversations in Online Discussion Forums 

    Aumayr, Erik; Jeffrey, Chan; Hayes, Conor (Fifth International AAAI Conference on Weblogs and Social Media, 2011-07-18)
    [no abstract available]
  • Relaxing the Basic KR&R Principles to Meet the Emergent Semantic Web 

    Novacek, Vit (CEUR-WS, 2008)
    The paper argues for an alternative, empirical (instead of analytical) approach to a Semantic Web-ready KR&R, motivated by the so far largely untackled need for a feasible emergent content processing.