Matches in ScholarlyData for { ?s ?p ?o. }
- 50 keyword "Data summaries".
- 50 keyword "Hypergraphs".
- 50 keyword "SPARQL query federation".
- 50 keyword "Source selection".
- 50 title "HiBISCuS: Hypergraph-Based Source Selection for SPARQL Endpoint Federation".
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- item-1 hasContent muhammad-saleem.
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- item-2 hasContent axel-cyrille-ngonga-ngomo.
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- 53 creator andreas-wagner.
- 53 creator thanh-tran.
- 53 creator veli-bicer.
- 53 type InProceedings.
- 53 label "Pay-as-you-go Approximate Join Top-k Processing for the Web of Data".
- 53 sameAs 53.
- 53 abstract "For effectively searching the Web of data, ranking results is a crucial. Top-k processing strategies have been proposed to allow an efficient processing of such ranked queries. These strategies aim at computing k top-ranked results without complete result materialization. However, for many applications result computation time is much more important than result accuracy and completeness. Thus, there is a strong need for approximated ranked results. Unfortunately, previous work on approximate top-k processing is not well-suited for the Web of data. In this paper, we propose the first approximate top-k join framework for Web data and queries. Our approach is very lightweight – neces- sary statistics are learned at runtime in a pay-as-you-go manner. We conducted extensive experiments on state-of-art RDF benchmarks. Our results are very promising: we could achieve up to 65% time savings, while maintaining a high precision/recall.".
- 53 hasAuthorList authorList.
- 53 isPartOf proceedings.
- 53 keyword "Approximate Query Processing".
- 53 keyword "Rank-aware Query Processing".
- 53 keyword "Top-k Join Processing".
- 53 title "Pay-as-you-go Approximate Join Top-k Processing for the Web of Data".
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- item-1 hasContent andreas-wagner.
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- item-2 hasContent veli-bicer.
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- item-3 hasContent thanh-tran.
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- 65 creator benjamin-zapilko.
- 65 creator brigitte-mathiak.
- 65 type InProceedings.
- 65 label "Object Property Matching utilizing the Overlap between Imported Ontologies".
- 65 sameAs 65.
- 65 abstract "Large scale Linked Data is often based on relational databases and thereby tends to be modeled with rich object properties, specifying the exact relationship between two objects, rather than a generic is-a or part-of relationship. We study this phenomenon on government issued statistical data, where a vested interest exists in matching such object properties for data integration. We leverage the fact that while the labeling of the properties is often heterogeneous, e.g. ex1:geo and ex2:location, they link to individuals of semantically similar code lists, e.g. country lists. State-of-the-art ontology matching tools do not use this effect and therefore tend to miss the possible correspondences. We enhance the state-of-the-art matching process by aligning the individuals of such imported ontologies separately and computing the overlap between them to improve the matching of the object properties. The matchers themselves are used as black boxes and are thus interchangeable. The new correspondences found with this method lead to an increase of recall up to 2.5 times on real world data, with only a minor loss in precision.".
- 65 hasAuthorList authorList.
- 65 isPartOf proceedings.
- 65 keyword "Linked Data".
- 65 keyword "Ontology Matching".
- 65 keyword "Property Matching".
- 65 keyword "Statistical Data".
- 65 title "Object Property Matching utilizing the Overlap between Imported Ontologies".
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- item-1 hasContent benjamin-zapilko.
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- item-2 hasContent brigitte-mathiak.
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- 67 creator ansgar-scherp.
- 67 creator johann-schaible.
- 67 creator thomas-gottron.
- 67 type InProceedings.
- 67 label "Survey on Common Strategies of Vocabulary Reuse in Linked Open Data Modeling".
- 67 sameAs 67.
- 67 abstract "The choice of which vocabulary to reuse when modeling and publishing Linked Open Data (LOD) is far from trivial. Until today, there is no study that investigates the different strategies of reusing vocabularies for LOD modeling.In this paper, we present the results of a survey with 79 participants that examines the most preferred strategies of vocabulary reuse of LOD modeling. Participants of our survey are LOD publishers and practitioners. Their task was to assess different vocabulary reuse strategies and explain their ranking decision. We found significant differences between the modeling strategies that range from reusing popular vocabularies, minimizing the number of vocabularies, and staying within one domain vocabulary. A very interesting insight is that the popularity in terms of how many data sources use a vocabulary is more important than total occurrence of individual classes and properties in the LOD cloud. Overall, the results of this survey help in better understanding the strategies how data engineers reuse vocabularies and may be used to develop future vocabulary engineering tools.".
- 67 hasAuthorList authorList.
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- 67 keyword "Empirical Survey".
- 67 keyword "Linked Open Data Modeling".
- 67 keyword "Vocabulary Reuse".
- 67 title "Survey on Common Strategies of Vocabulary Reuse in Linked Open Data Modeling".
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- item-1 hasContent johann-schaible.
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- item-2 hasContent thomas-gottron.
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- item-3 hasContent ansgar-scherp.
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- 68 creator adrian-paschke.
- 68 creator kia-teymourian.