rdf PDF: 1 to 10 of 483 results fetched - page 1 [ao]

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10663112 RDF

www.archive.org/details/10663112RDF...
RDF_FileTest
Published on 06/18/2018
Document details: 43 downloads.

9apr rdf network

www.archive.org/details/9apr_rdf_network...
9apr rdf network
Published on 09/27/2015
Document details: 1 page. 35 downloads.

RDF 1985 manual

www.archive.org/details/c64man_rdf-1985...
Source:  http://www.c64sets.com/rdf_1985.html
Published on 10/11/2018
Document details: 8 pages. 33 downloads.

Report on RDF Network

www.archive.org/details/1941_9apr_rdf_network...
Report on RDF Network | 9 April 1941 (Release 5)
Published on 05/08/2011
Document details: 1 pages. 51 downloads.

Incomplete Information in RDF

www.archive.org/details/arxiv-1209.3756...
We extend RDF with the ability to represent property values that exist, but are unknown or partially known, using constraints. Following ideas from the incomplete information literature, we develop a semantics for this extension of RDF, called RDFi, and study SPARQL query evaluation in this framework.
Published on 09/17/2013
Document details: 1 pages. 30 downloads.

The RDF Virtual Machine

www.archive.org/details/arxiv-0802.3492...
The Resource Description Framework (RDF) is a semantic network data model that is used to create machine-understandable descriptions of the world and is the basis of the Semantic Web. This article discusses the application of RDF to the representation of computer software and virtual computing machines. The Semantic Web is posited as not only a web of data, but also as a web of programs and processes.
Published on 09/20/2013
Document details: 1 pages. 60 downloads.

Co-evolution of RDF Datasets

www.archive.org/details/arxiv-1601.05270...
Linking Data initiatives have fostered the publication of large number of RDF datasets in the Linked Open Data (LOD) cloud, as well as the development of query processing infrastructures to access these data in a federated fashion. However, different experimental studies have shown that availability of LOD datasets cannot be always ensured, being RDF data replication required for envisioning reliable federated query frameworks. Albeit enhancing data availability, RDF data replication requires synchronization and conflict resolution when replicas and source datasets are allowed to change data over time, i.e., co-evolution management needs to be provided to ensure consistency. In this paper, we tackle the problem of RDF data co-evolution and devise an approach for conflict resolution during co-evolution of RDF datasets. Our proposed approach is property-oriented and allows for exploiting semantics about RDF properties during co-evolution management. The quality of our approach is empirically evaluated in different scenarios on the DBpedia-live dataset. Experimental results suggest that proposed proposed techniques have a positive impact on the quality of data in source datasets and replicas.
Published on 06/29/2018
Document details: 1 pages. 60 downloads.

RDF-Hunter: Automatically Crowdsourcing the Execution of Queries Against RDF Data Sets

www.archive.org/details/arxiv-1503.02911...
In the last years, a large number of RDF data sets has become available on the Web. However, due to the semi-structured nature of RDF data, missing values affect answer completeness of queries that are posed against this data. To overcome this limitation, we propose RDF-Hunter, a novel hybrid query processing approach that brings together machine and human computation to execute queries against RDF data. We develop a novel quality model and query engine in order to enable RDF-Hunter to on the fly decide which parts of a query should be executed through conventional technology or crowd computing. To evaluate RDF-Hunter, we created a collection of 50 SPARQL queries against the DBpedia data set, executed them using our hybrid query engine, and analyzed the accuracy of the outcomes obtained from the crowd. The experiments clearly show that the overall approach is feasible and produces query results that reliably and significantly enhance completeness of automatic query processing responses.
Published on 06/26/2018
Document details: 1 pages. 2 downloads.

Taming Subgraph Isomorphism for RDF Query Processing

www.archive.org/details/arxiv-1506.01973...
RDF data are used to model knowledge in various areas such as life sciences, Semantic Web, bioinformatics, and social graphs. The size of real RDF data reaches billions of triples. This calls for a framework for efficiently processing RDF data. The core function of processing RDF data is subgraph pattern matching. There have been two completely different directions for supporting efficient subgraph pattern matching. One direction is to develop specialized RDF query processing engines exploiting the properties of RDF data for the last decade, while the other direction is to develop efficient subgraph isomorphism algorithms for general, labeled graphs for over 30 years. Although both directions have a similar goal (i.e., finding subgraphs in data graphs for a given query graph), they have been independently researched without clear reason. We argue that a subgraph isomorphism algorithm can be easily modified to handle the graph homomorphism, which is the RDF pattern matching semantics, by just removing the injectivity constraint. In this paper, based on the state-of-the-art subgraph isomorphism algorithm, we propose an in-memory solution, TurboHOM++, which is tamed for the RDF processing, and we compare it with the representative RDF processing engines for several RDF benchmarks in a server machine where billions of triples can be loaded in memory. In order to speed up TurboHOM++, we also provide a simple yet effective transformation and a series of optimization techniques. Extensive experiments using several RDF benchmarks show that TurboHOM++ consistently and significantly outperforms the representative RDF engines. Specifically, TurboHOM++ outperforms its competitors by up to five orders of magnitude.
Published on 06/27/2018
Document details: 1 pages. 2 downloads.

Validating RDF with Shape Expressions

www.archive.org/details/arxiv-1404.1270...
We propose shape expression schema (ShEx), a novel schema formalism for describing the topology of an RDF graph that uses regular bag expressions (RBEs) to define constraints on the admissible neighborhood for the nodes of a given type. We provide two alternative semantics, multi- and single-type, depending on whether or not a node may have more than one type. We study the expressive power of ShEx and study the complexity of the validation problem. We show that the single-type semantics is strictly more expressive than the multi-type semantics, single-type validation is generally intractable and multi-type validation is feasible for a small class of RBEs. To further curb the high computational complexity of validation, we propose a natural notion of determinism and show that multi-type validation for the class of deterministic schemas using single-occurrence regular bag expressions (SORBEs) is tractable. Finally, we consider the problem of validating only a fragment of a graph with preassigned types for some of its nodes, and argue that for deterministic ShEx using SORBEs, multi-type validation can be performed efficiently and single-type validation can be performed with a single pass over the graph.
Published on 06/29/2018
Document details: 1 pages. 1 download.
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