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  4. SQCFramework: SPARQL Query Containment Benchmark Generation Framework
 
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2017
Conference Paper
Title

SQCFramework: SPARQL Query Containment Benchmark Generation Framework

Abstract
Query containment is a fundamental problem in data management with its main application being in global query optimization. A number of SPARQL query containment solvers for SPARQL have been recently developed. To the best of our knowledge, the Query Containment Benchmark (QC-Bench) is the only benchmark for evaluating these containment solvers. However, this benchmark contains a fixed number of synthetic queries, which were handcrafted by its creators. We propose SQCFramework, a SPARQL query containment benchmark generation framework which is able to generate customized SPARQL containment benchmarks from real SPARQL query logs. The framework is flexible enough to generate benchmarks of varying sizes and according to the user-defined criteria on the most important SPARQL features to be considered for query containment benchmarking. This is achieved using different clustering algorithms. We compare state-of-the-art SPARQL query containment solvers by using different query containment benchmarks generated from DBpedia and Semantic Web Dog Food query logs. In addition, we analyze the quality of the different benchmarks generated by SQCFramework.
Author(s)
Saleem, Muhammad
Stadler, Claus
Mehmood, Qaiser
Lehmann, Jens  
Ngonga Ngomo, Axel-Cyrille  
Mainwork
K-CAP 2017. Proceedings of the Knowledge Capture Conference  
Conference
International Conference on Knowledge Capture (K-CAP) 2017  
Link
Link
DOI
10.1145/3148011.3148017
Language
English
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
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