Matches in ScholarlyData for { ?s ?p ?o. }
- 7 creator maxime-lefrancois.
- 7 type InProceedings.
- 7 label "Supporting Arbitrary Custom Datatypes in RDF and SPARQL".
- 7 sameAs 7.
- 7 abstract "In the Resource Description Framework, literals are composed of a UNICODE string (the lexical form), a datatype IRI, and optionally, when the datatype IRI is rdf:langString, a language tag. Any IRI can take the place of a datatype IRI, but the specification only defines the precise meaning of a literal when the datatype IRI is among a predefined subset. Custom datatypes have reported use on the Web of Data, and show some advantages in representing some classical structures. Yet, their support by RDF processors is rare and implementation specific. In this paper, we first present the minimal set of functions that should be defined in order to make a custom datatype usable in query answering and reasoning. Based on this, we discuss solutions that would enable: (i) data publishers to publish the definition of arbitrary custom datatypes on the Web, and (ii) generic RDF processor or SPARQL query engine to discover custom datatypes on-the-fly, and to perform operations on them accordingly. Finally, we detail a concrete solution that targets arbitrarily complex custom datatypes, we overview its implementation in Jena and ARQ, and we report the results of an experiment on a real world DBpedia use case. ".
- 7 hasAuthorList authorList.
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- 7 title "Supporting Arbitrary Custom Datatypes in RDF and SPARQL".
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- item-1 hasContent maxime-lefrancois.
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- item-2 hasContent antoine-zimmermann.
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- 81 creator axel-cyrille-ngonga-ngomo.
- 81 creator mofeed-hassan.
- 81 type InProceedings.
- 81 label "The Lazy Traveling Salesman -- Memory Management for Large-Scale Link Discovery".
- 81 sameAs 81.
- 81 abstract "Links between knowledge bases build the backbone of the Linked Data Web. Several time-efficient algorithms have hence been developed for computing links between knowledge bases. However, these approaches pay little attention to the fact that very large datasets cannot be held in the main memory of most computing devices. In this paper, we address this research gap by presenting a generic memory management approach that can by combined with any blocking- or filtering-based algorithm for Link Discovery. We show that the problem at hand is a variation of the Traveling Salesman Problem and is thus NP-complete. We thus provide efficient best-effort graph-based algorithms that allow scheduling link discovery tasks efficiently. We combine these algorithms with caching approaches that allow for loading required data from massive storage. Our evaluation on real data shows that our approach allows computing links between large amounts of resources efficiently even when using commodity hardware.".
- 81 hasAuthorList authorList.
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- 81 title "The Lazy Traveling Salesman -- Memory Management for Large-Scale Link Discovery".
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- item-1 hasContent axel-cyrille-ngonga-ngomo.
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- item-2 hasContent mofeed-hassan.
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- 89 creator allel-hadjali.
- 89 creator geraud-fokou.
- 89 creator mickael-baron.
- 89 creator stephane-jean.
- 89 type InProceedings.
- 89 label "RDF Query Relaxation Strategies Based on Failure Causes".
- 89 sameAs 89.
- 89 abstract "Recent advances in Web-information extraction have led to the creation of several large Knowledge Bases (KBs). Querying these KBs often results in empty answers that do not serve the users' needs. Relaxation of the failing queries is one of the cooperative techniques used to retrieve alternative results. Most of the previous work on RDF query relaxation compute a set of relaxed queries and execute them in a similarity-based ranking order. Thus, these approaches relax an RDF query without knowing its Failure Causes (FCs). In this paper, we study the interest of identifying these FCs to speed up the query relaxation process. We propose three relaxation strategies based on various information levels about the FCs of the user query and of its relaxed queries as well. A set of experiments conducted on the LUBM benchmark show the interest of our proposal in comparison with a state-of-the-art algorithm.".
- 89 hasAuthorList authorList.
- 89 isPartOf proceedings.
- 89 title "RDF Query Relaxation Strategies Based on Failure Causes".
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- item-1 type ListItem.
- item-1 hasContent geraud-fokou.
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- item-2 hasContent stephane-jean.
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- item-3 type ListItem.
- item-3 hasContent allel-hadjali.
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- item-4 hasContent mickael-baron.
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- 1 creator markus-bischoff.
- 1 creator markus-luczak-roesch.
- 1 type InProceedings.
- 1 label "Statistical Analysis of Web of Data Usage".
- 1 sameAs 1.
- 1 abstract "The Linked Data initiative gained momentum inside as well as outside of theresearch community. Thus, it is already an accepted research issue to investigate usage mining in the context ofthe Web of Data from various perspectives. We are currently working onan approach that applies such usage mining methods and analysis to support ontology and datasetmaintenance tasks. This paper presents one part of this work, namely a methodto detect errors or weaknesses within ontologies used for Linked Data populationbased on statistics and network visualizations. We contribute a detailed description of a log file preprocessing algorithm for Web of Data endpoints, a set of statistical measures that help to visualize different usage aspects, and an examplary analysis of one of the most prominent Linked Data set -- DBpedia -- aimed to show the feasibility and the potential of our approach.".
- 1 hasAuthorList authorList.
- 1 isPartOf proceedings.
- 1 keyword "linked data".
- 1 keyword "ontology maintenance".
- 1 keyword "web usage mining".
- 1 title "Statistical Analysis of Web of Data Usage".
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- item-1 hasContent markus-luczak-roesch.
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- item-2 hasContent markus-bischoff.
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- 10 creator natalya-noy.
- 10 creator timothy-redmond.
- 10 type InProceedings.
- 10 label "Protege 4 Difference Engine".
- 10 sameAs 10.
- 10 abstract "As ontologies evolve, it becomes important to be able to dis-cover how they have changed over time. In the recent past there havebeen a few very useful tools based on the Manchester OWL API thataddress this issue. However, these new tools do not take into accounthow to align entities in two ontologies when the names of the entitieshave changed. In this case, we need to be able to discover the alignmentbetween the entities in the two ontologies before can match up the struc-tures in the two ontologies. In this paper, we describe a highly optimizedpluggable difference engine that searches for alignments between entitiesin different ontology versions and applies those alignments to display thedifferences in the ontologies. We discuss our experiences applying thetools to a selection of ontologies from the BioPortal ontology reposi-tory, including the performance and accuracy of the tool.".