Matches in ScholarlyData for { ?s ?p ?o. }
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- paper-30 type InProceedings.
- paper-30 label "Domain-aware Ontology Matching".
- paper-30 sameAs paper-30.
- paper-30 abstract "The inherent heterogeneity of datasets on the Semantic Web has created a need to interlink them, and several tools have emerged that automate this task. In this paper we are interested in what happens if we enrich these matching tools with knowledge of the domain of the ontologies. We explore how to express the notion of a domain in terms usable for an ontology matching tool, and we examine various methods to decide what constitutes the domain of a given dataset. We show how we can use this in a matching tool, and study the effect of domain knowledge on the quality of the alignment. We perform evaluations for two scenarios: Last.fm artists and UMLS medical terms. To quantify the added value of domain knowledge, we compare our domain-aware matching approach to a standard approach based on a manually created reference alignment. The results indicate that the proposed domain-aware approach indeed outperforms the standard approach, with a large effect on ambiguous concepts but a much smaller effect on unambiguous concepts.".
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- paper-30 title "Domain-aware Ontology Matching".
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- item-1 hasContent kristian-slabbekoorn.
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- item-2 hasContent laura-hollink.
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- item-3 hasContent geert-jan-houben.
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- paper-31 type InProceedings.
- paper-31 label "Robust Runtime Optimization and Skew-Resistant Execution of Analytical SPARQL Queries on Pig".
- paper-31 sameAs paper-31.
- paper-31 abstract "We describe a system that incrementally translates SPARQL queries to Pig Latin and executes them on a Hadoop cluster. This system is designed to work efficiently on complex queries with many self-joins over huge datasets, avoiding job failures even in the case of joins with unexpected high-value skew. To be robust against cost estimation errors, our system interleaves query optimization with query execution, determining the next steps to take based on data samples and statistics gathered during the previous step. Furthermore, we have developed a novel skew-resistant join algorithm that replicates tuples corresponding to popular keys. We evaluate the effectiveness of our approach both on a synthetic benchmark known to generate complex queries (BSBM-BI) as well as on a Yahoo! case of data analysis using RDF data crawled from the web. Our results indicate that our system is indeed capable of processing huge datasets without pre-computed statistics while exhibiting good load-balancing properties.".
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- paper-31 title "Robust Runtime Optimization and Skew-Resistant Execution of Analytical SPARQL Queries on Pig".
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- item-2 hasContent jacopo-urbani.
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- item-3 hasContent peter-boncz.
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- item-4 hasContent peter-mika.
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- paper-32 type InProceedings.
- paper-32 label "SPLODGE: Systematic Generation of SPARQL Benchmark Queries for Linked Open Data".
- paper-32 sameAs paper-32.
- paper-32 abstract "The distributed and heterogeneous nature of Linked Open Data requires flexible and federated techniques for query evaluation. In order to evaluate current federation querying approaches a general methodology for conducting benchmarks is mandatory. In this paper, we present a classification methodology for federated SPARQL queries. This methodology can be used by developers of federated querying approaches to compose a set of test benchmarks that cover diverse characteristics of different queries and allows for comparability. We further develop a heuristic called SPLODGE for automatic generation of benchmark queries that is based on this methodology and takes into account the number of sources to be queried and several complexity parameters. We evaluate the adequacy of our methodology and the query generation strategy by applying them on the 2011 billion triple challenge data set.".
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- paper-32 title "SPLODGE: Systematic Generation of SPARQL Benchmark Queries for Linked Open Data".
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- item-1 hasContent olaf-goerlitz.
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- item-2 hasContent matthias-thimm.
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- item-3 hasContent steffen-staab.
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- paper-33 type InProceedings.
- paper-33 label "RDFS Reasoning on Massively Parallel Hardware".
- paper-33 sameAs paper-33.
- paper-33 abstract "Recent developments in hardware have shown an increase in parallelism as opposed to clock rates. In order to fully exploit these new avenues of performance improvement, computationally expensive workloads have to be expressed in a way that allows for fine-grained parallelism. In this paper, we address the problem of describing RDFS entailment in such a way. Different from previous work on parallel RDFS reasoning, we assume a shared memory architecture. We analyze the problem of duplicates that naturally occur in RDFS reasoning and develop strategies towards its mitigation, exploiting all levels of our architecture. We implement and evaluate our approach on two real-world datasets and study its performance characteristics on different levels of parallelization. We conclude that RDFS entailment lends itself well to parallelization but can benefit even more from careful optimizations that take into account intricacies of modern parallel hardware.".
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- paper-33 title "RDFS Reasoning on Massively Parallel Hardware".
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- item-1 hasContent norman-heino.
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