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Efficient source selection and benchmarking for SPARQL Endpoint Query Federation / Muhammad Saleem.

By: Contributor(s): Material type: TextTextSeries: Studies on the Semantic Web ; vol. 026.Publisher: Amsterdam, Netherlands : IOS Press, 2018Description: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781614998402
  • 161499840X
Subject(s): Genre/Form: DDC classification:
  • 005.74 23
LOC classification:
  • QA76.73.S62
Online resources:
Contents:
Intro; Title Page; Acknowledgments; Contents; Abstract; Introduction; Federated SPARQL Query Processing; The Need for Efficient Source Selection; The Need for More Comprehensive SPARQL Benchmarks; Contributions; Chapter Overview; Basic Concepts and Notation; Semantic Web; URIs, RDF; SPARQL Query Language; Triplestore; SPARQL Syntax, Semantic and Notation; State of the Art; Federation systems evaluations; Benchmarks; Federated engines public survey; Survey Design; Discussion of the survey results; Details of selected systems; Overview of the selected approaches; Performance Variables.
EvaluationExperimental setup; Evaluation criteria; Experimental results; Discussion; Effect of the source selection time; Effect of the data partitioning; Hypergraph-Based Source Selection; Problem Statement; HiBISCuS; Queries as Directed Labelled Hypergraphs; Data Summaries; Source Selection Algorithm; Pruning approach; Evaluation; Experimental Setup; Experimental Results; Trie-based Source Selection; TBSS; TBSS Data Summaries; TBSS Source Selection Algorithm; TBSS Pruning approach; QUETSAL; Quetsal's Architecture; Quetsal's SPARQL 1.1 Query Re-writing; Evaluation; Experimental Setup.
Experimental ResultsDuplicate-Aware Source Selection; DAW; Min-Wise Independent Permutations (MIPs); DAW Index; DAW Federated Query Processing; Experimental Evaluation; Experimental Setup; Experimental Results; Policy-Aware Source Selection; Motivating Scenario; Methodology and Architecture; Evaluation; Experimental Setup; Experimental Results; Data Distribution-Based Source Selection; Motivation; Biological query example; Methods; Transforming TCGA data to RDF; Linking TCGA to the LOD cloud; TCGA data workflow and schema; Data distribution and load balancing.
TopFed federated query processing approachSource selection; Results and discussion; Evaluation; Availability of supporting data; LargeRDFBench: SPARQL Federation Benchmark; Background; The Need of More Comprehensive SPARQL Federation Benchmark; Benchmark Description; Benchmark Datasets; Benchmark Queries; Performance Metrics; Evaluation; Experimental Setup; SPARQL 1.0 Experimental Results; SPARQL 1.1 Experimental Results; FEASIBLE: SPARQL Benchmarks Generation Framework; Key SPARQL Features; A Comparison of Existing Triple Stores Benchmarks and Query Logs; FEASIBLE Benchmark Generation.
Data Set CleaningNormalization of Features Vectors; Query Selection; Complexity Analysis; Evaluation and Results; Composite Error Estimation; Experimental Setup; Experimental Results; Conclusion; HiBISCuS; TBSS/Quetsal; DAW; SAFE; TopFed; LargeRDFBench; FEASIBLE; Bibliography.
Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
eBook eBook e-Library EBSCO Computers Available
Total holds: 0

Online resource; title from PDF title page (EBSCO, viewed September 27, 2018).

Includes bibliographical references.

Intro; Title Page; Acknowledgments; Contents; Abstract; Introduction; Federated SPARQL Query Processing; The Need for Efficient Source Selection; The Need for More Comprehensive SPARQL Benchmarks; Contributions; Chapter Overview; Basic Concepts and Notation; Semantic Web; URIs, RDF; SPARQL Query Language; Triplestore; SPARQL Syntax, Semantic and Notation; State of the Art; Federation systems evaluations; Benchmarks; Federated engines public survey; Survey Design; Discussion of the survey results; Details of selected systems; Overview of the selected approaches; Performance Variables.

EvaluationExperimental setup; Evaluation criteria; Experimental results; Discussion; Effect of the source selection time; Effect of the data partitioning; Hypergraph-Based Source Selection; Problem Statement; HiBISCuS; Queries as Directed Labelled Hypergraphs; Data Summaries; Source Selection Algorithm; Pruning approach; Evaluation; Experimental Setup; Experimental Results; Trie-based Source Selection; TBSS; TBSS Data Summaries; TBSS Source Selection Algorithm; TBSS Pruning approach; QUETSAL; Quetsal's Architecture; Quetsal's SPARQL 1.1 Query Re-writing; Evaluation; Experimental Setup.

Experimental ResultsDuplicate-Aware Source Selection; DAW; Min-Wise Independent Permutations (MIPs); DAW Index; DAW Federated Query Processing; Experimental Evaluation; Experimental Setup; Experimental Results; Policy-Aware Source Selection; Motivating Scenario; Methodology and Architecture; Evaluation; Experimental Setup; Experimental Results; Data Distribution-Based Source Selection; Motivation; Biological query example; Methods; Transforming TCGA data to RDF; Linking TCGA to the LOD cloud; TCGA data workflow and schema; Data distribution and load balancing.

TopFed federated query processing approachSource selection; Results and discussion; Evaluation; Availability of supporting data; LargeRDFBench: SPARQL Federation Benchmark; Background; The Need of More Comprehensive SPARQL Federation Benchmark; Benchmark Description; Benchmark Datasets; Benchmark Queries; Performance Metrics; Evaluation; Experimental Setup; SPARQL 1.0 Experimental Results; SPARQL 1.1 Experimental Results; FEASIBLE: SPARQL Benchmarks Generation Framework; Key SPARQL Features; A Comparison of Existing Triple Stores Benchmarks and Query Logs; FEASIBLE Benchmark Generation.

Data Set CleaningNormalization of Features Vectors; Query Selection; Complexity Analysis; Evaluation and Results; Composite Error Estimation; Experimental Setup; Experimental Results; Conclusion; HiBISCuS; TBSS/Quetsal; DAW; SAFE; TopFed; LargeRDFBench; FEASIBLE; Bibliography.

WorldCat record variable field(s) change: 650

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