SPARQL Query Generator (SQG)

被引：9

作者：

Chen, Yanji ^{[1
]}

Kokar, Mieczyslaw M. ^{[1
]}

Moskal, Jakub J. ^{[2
]}

机构：

[1] Northeastern Univ, Dept Elect & Comp Engn, Boston, MA 02115 USA

[2] VIStology Inc, Framingham, MA USA

来源：

JOURNAL ON DATA SEMANTICS | 2021年 / 10卷 / 3-4期

关键词：

Synthetic SPARQL query generation; Ontology-based descriptions; Cognitive radios; OWL axioms; Jena ARQ; SPARQL query evaluation;

D O I：

10.1007/s13740-021-00133-y

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper describes a program-SPARQL Query Generator (SQG)-which takes as input an OWL ontology, a set of object descriptions in terms of this ontology and an OWL class as the context, and generates relatively large numbers of queries about various types of descriptions of objects expressed in RDF/OWL. The intent is to use SQG in evaluating data representation and retrieval systems from the perspective of OWL semantics coverage. While there are many benchmarks for assessing the efficiency of data retrieval systems, none of the existing solutions for SPARQL query generation focus on the coverage of the OWL semantics. Some are not scalable since manual work is needed for the generation process; some do not consider (or totally ignore) the OWL semantics in the ontology/instance data or rely on large numbers of real queries/datasets that are not readily available in our domain of interest. Our experimental results show that SQG performs reasonably well with generating large numbers of queries and guarantees a good coverage of OWL axioms included in the generated queries.

引用

页码：291 / 307

页数：17

共 41 条

[11]

Arenas M, 2010, SEMANTIC WEB INFORMATION MANAGEMENT, P281, DOI 10.1007/978-3-642-04329-1_13

[12]

Arias M., 2011, USEWOD

[13] QA3: A natural language approach to question answering over RDF data cubes [J].

Atzori, Maurizio ;

Mazzeo, Giuseppe M. ;

Zaniolo, Carlo .

SEMANTIC WEB, 2019, 10 (03) :587-604

[14] gMark: Schema-Driven Generation of Graphs and Queries [J].

Bagan, Guillaume ;

Bonifati, Angela ;

Ciucanu, Radu ;

Fletcher, George H. L. ;

Lemay, Aurelien ;

Advokaat, Nicky .

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2017, 29 (04) :856-869

[15] An Analytical Study of Large SPARQL Query Logs [J].

Bonifati, Angela ;

Martens, Wim ;

Timm, Thomas .

PROCEEDINGS OF THE VLDB ENDOWMENT, 2017, 11 (02) :149-161

[16] Created in Close Interaction with the Industry: The Smart Appliances REFerence (SAREF) Ontology [J].

Daniele, Laura ;

den Hartog, Frank ;

Roes, Jasper .

FORMAL ONTOLOGIES MEET INDUSTRY, FOMI 2015, 2015, 225 :100-112

[17] Ontology-Based Device Descriptions and Device Repository for Building Automation Devices [J].

Dibowski, Henrik ;

Kabitzsch, Klaus .

EURASIP JOURNAL ON EMBEDDED SYSTEMS, 2011, (01)

[18]

Erling O., 2009, NETWORKED KNOWLEDGE, P7, DOI [10.1007/978-3-642-02184-8_2, DOI 10.1007/978-3-642-02184-82, DOI 10.1007/978-3-642-02184-8_2]

[19]

Gorlitz Olaf, 2012, The Semantic Web. 11th International Semantic Web Conference (ISWC 2012). Proceedings, P116, DOI 10.1007/978-3-642-35176-1_8

[20] LUBM: A benchmark for OWL knowledge base systems [J].

Guo, YB ;

Pan, ZX ;

Heflin, J .

JOURNAL OF WEB SEMANTICS, 2005, 3 (2-3) :158-182

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