Search (6 results, page 1 of 1)

  • × theme_ss:"Semantische Interoperabilität"
  • × theme_ss:"Wissensrepräsentation"
  • × type_ss:"el"
  1. Bittner, T.; Donnelly, M.; Winter, S.: Ontology and semantic interoperability (2006) 0.02 
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    Date
    3.12.2016 18:39:22
    Type
    a
  2. Hoekstra, R.: BestMap: context-aware SKOS vocabulary mappings in OWL 2 (2009) 0.00 
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    Abstract
    This paper describes an approach to SKOS vocabulary mapping that takes into account the context in which vocabulary terms are used in annotations. The standard vocabulary mapping properties in SKOS only allow for binary mappings between concepts. In the BestMap ontology, annotated resources are the contexts in which annotations coincide and allow for a more fine grained control over when mappings hold. A mapping between two vocabularies is defined as a class that groups descriptions of a resource. We use the OWL 2 features for property chains, disjoint properties, union, intersection and negation together with careful use of equivalence and subsumption to specify these mappings.
  3. Hollink, L.; Assem, M. van; Wang, S.; Isaac, A.; Schreiber, G.: Two variations on ontology alignment evaluation : methodological issues (2008) 0.00 
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    Abstract
    Evaluation of ontology alignments is in practice done in two ways: (1) assessing individual correspondences and (2) comparing the alignment to a reference alignment. However, this type of evaluation does not guarantee that an application which uses the alignment will perform well. In this paper, we contribute to the current ontology alignment evaluation practices by proposing two alternative evaluation methods that take into account some characteristics of a usage scenario without doing a full-fledged end-to-end evaluation. We compare different evaluation approaches in three case studies, focussing on methodological issues. Each case study considers an alignment between a different pair of ontologies, ranging from rich and well-structured to small and poorly structured. This enables us to conclude on the use of different evaluation approaches in different settings.
  4. Bandholtz, T.; Schulte-Coerne, T.; Glaser, R.; Fock, J.; Keller, T.: iQvoc - open source SKOS(XL) maintenance and publishing tool (2010) 0.00 
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    Abstract
    iQvoc is a new open source SKOS-XL vocabulary management tool developed by the Federal Environment Agency, Germany, and innoQ Deutschland GmbH. Its immediate purpose is maintaining and publishing reference vocabularies in the upcoming Linked Data cloud of environmental information, but it may be easily adapted to host any SKOS- XL compliant vocabulary. iQvoc is implemented as a Ruby on Rails application running on top of JRuby - the Java implementation of the Ruby Programming Language. To increase the user experience when editing content, iQvoc uses heavily the JavaScript library jQuery.
    Type
    a
  5. Krötzsch, M.; Hitzler, P.; Ehrig, M.; Sure, Y.: Category theory in ontology research : concrete gain from an abstract approach (2004 (?)) 0.00 
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    Abstract
    The focus of research on representing and reasoning with knowledge traditionally has been on single specifications and appropriate inference paradigms to draw conclusions from such data. Accordingly, this is also an essential aspect of ontology research which has received much attention in recent years. But ontologies introduce another new challenge based on the distributed nature of most of their applications, which requires to relate heterogeneous ontological specifications and to integrate information from multiple sources. These problems have of course been recognized, but many current approaches still lack the deep formal backgrounds on which todays reasoning paradigms are already founded. Here we propose category theory as a well-explored and very extensive mathematical foundation for modelling distributed knowledge. A particular prospect is to derive conclusions from the structure of those distributed knowledge bases, as it is for example needed when merging ontologies
    Type
    a
  6. Wenige, L.; Ruhland, J.: Similarity-based knowledge graph queries for recommendation retrieval (2019) 0.00 
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    Abstract
    Current retrieval and recommendation approaches rely on hard-wired data models. This hinders personalized cus-tomizations to meet information needs of users in a more flexible manner. Therefore, the paper investigates how similarity-basedretrieval strategies can be combined with graph queries to enable users or system providers to explore repositories in the LinkedOpen Data (LOD) cloud more thoroughly. For this purpose, we developed novel content-based recommendation approaches.They rely on concept annotations of Simple Knowledge Organization System (SKOS) vocabularies and a SPARQL-based querylanguage that facilitates advanced and personalized requests for openly available knowledge graphs. We have comprehensivelyevaluated the novel search strategies in several test cases and example application domains (i.e., travel search and multimediaretrieval). The results of the web-based online experiments showed that our approaches increase the recall and diversity of rec-ommendations or at least provide a competitive alternative strategy of resource access when conventional methods do not providehelpful suggestions. The findings may be of use for Linked Data-enabled recommender systems (LDRS) as well as for semanticsearch engines that can consume LOD resources. (PDF) Similarity-based knowledge graph queries for recommendation retrieval. Available from: https://www.researchgate.net/publication/333358714_Similarity-based_knowledge_graph_queries_for_recommendation_retrieval [accessed May 21 2020].
    Type
    a

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