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Research on SPARQL Semantic Query Technology Based on Knowledge Hybrid Storage

Published: 05 January 2022 Publication History

Abstract

At present, knowledge graphs are usually expressed in RDF and given semantics. SPARQL is a semantic query language recommended by W3C. With the development of the Semantic Web technology, the current different storage modes for knowledge management mainly have the incompatibility of support for massive knowledge storage and semantic query standards. For example, Neo4j cannot use SPARQL for semantic query. Aiming at the low efficiency of technology fusion query conversion under the knowledge storage hybrid storage mode, this paper introduces the Apache TinkerPop graph calculation framework to build a bridge between RDF graphs and attribute graphs, and proposes a method for converting SPARQL queries to Gremlin attribute graph queries. Realize the semantic query ability under the massive knowledge storage, and make up for the shortcomings of different storage modes. In addition, TinkerPop must use a certain constant key value for binding query to expand to meet the completeness requirement of knowledge query. Finally, the experiment was verified by building a microservice API with Spring Boot.

References

[1]
E. Prud'hommeaux and A. Seaborne. SPARQL query language for RDF. Technical report, World Wide Web Consortium, October 2004.URL http://www.w3.org/TR/rdf-sparql-query/.
[2]
M.A. Rodriguez and P. Neubauer, The Graph Traversal Pattern,in: Graph Data Management: Techniques and Applications.,IGI Global, 2011.
[3]
The Authoritative Guide to Neo4j / Editor-in-Chief Zhang Zhi.-Beijing: Tsinghua University Press, 2017.
[4]
B. Yu, Y. Zhang and H. Sun, "Research on Knowledge Storage and Query Technology Based on General Graph Data Processing Framework," 2021 13th International Conference on Communication Software and Networks (ICCSN), 2021, pp. 305-309.
[5]
S. Das, J. Srinivasan, M. Perry, E.I. Chong and J. Banerjee, ATale of Two Graphs: Property Graphs as RDF in Oracle., in:EDBT, 2014.
[6]
M. Rodriguez-Muro and M. Rezk, Efficient SPARQL-to-SQL with R2RML mappings, Web Semantics: Science, Services and Agents on the World Wide Web 33 (2015).
[7]
D. Calvanese, B. Cogrel, S. Komla-Ebri, R. Kontchakov,D. Lanti, M. Rezk, M. Rodriguez-Muro and G. Xiao, Ontop:Answering SPARQL queries over relational databases, Semantic Web 8(3) (2017), 471–487.
[8]
Berners-Lee T, Hendler J, Lassila O. The semantic web[J]. Scientific american, 2001, 284(5): 28-37.
[9]
Thakkar, Harsh & Punjani, Dharmen & Keswani, Yashwant & Lehmann, Jens & Auer, Sören. (2018). A Stitch in Time Saves Nine – SPARQL querying of Property Graphs using Gremlin Traversals.
[10]
Le W, Kementsietsidis A, Duan S, et al. Scalable multi-query optimization for SPARQL[C]//Data Engineering (ICDE), 2012 IEEE 28th International Conference on. IEEE, 2012: 666-677.
[11]
R. Angles, M. Arenas, P. Barceló, A. Hogan, J.L. Reutter and D. Vrgoc, Foundations of Modern Graph Query Languages,CoRR abs/1610.06264 (2016).
[12]
M. Saleem, Y. Khan, A. Hasnain, I. Ermilov and A.N. Ngomo,A fine-grained evaluation of SPARQL endpoint federation systems, Semantic Web 7 (2015).
[13]
Thakkar H, D Punjani, Auer S, Towards an Integrated Graph Algebra for Graph Pattern Matching with Gremlin (Extended Version)[J]. 2019.
[14]
Apache TinkerPop.http://tinkerpop.apache.org.
[15]
Rodriguez, Marko A . The Gremlin graph traversal machine and language (invited talk). ACM, 2015:1-10.
[16]
H. Thakkar, D. Punjani, J. Lehmann and S. Auer, KillingTwo Birds with One Stone – Querying Property Graphs using SPARQL via GREMLINATOR, CoRR abs/1801.09556(2018).
[17]
J. M. Almendros-Jiménez, A. Becerra-Terón and G. Moreno, "A fuzzy extension of SPARQL based on fuzzy sets and aggregators", 2017 IEEE International Conference on Fuzzy Systems FUZZ-IEEE, pp. 1-6, 2017.
[18]
J. Lehmann, G. Sejdiu, L. Bühmann, P. Westphal, C. Stadler,I. Ermilov, S. Bin, N. Chakraborty, M. Saleem and A.-C.N. Ngomo, Distributed Semantic Analytics using the SANSA Stack, in: Proceedings of the 16th International Semantic Web Conference (ISWC), Springer, 2017, pp. 147–155
[19]
Song F, Corby O . Heuristics-based SPARQL Query Planning[J]. Inria Sophia Antipolis I3s, 2014.
[20]
Fuqi Song and Olivier Corby. Extended Query Pattern Graph and Heuristics - based SPARQL Query Planning[J]. Procedia Computer Science, 2015, 60 : 302-311.
[21]
R. Angles, P.A. Boncz, J. Larriba-Pey, The linked data benchmark council: a graph and RDF industry benchmarking effort, SIGMOD Record (2014).
[22]
Gharzouli M, Boufaida M . PM4SWS: A P2P Model for Semantic Web Services Discovery and Composition[J]. Journal of Advances in Information Technology, 2011, 2(1).
[23]
Improved Semantic Representation and Search Techniques in a Document Retrieval System Design[J]. Journal of Advances in Information Technology, 2015, 6(3):146-150.

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cover image ACM Other conferences
ICACS '21: Proceedings of the 5th International Conference on Algorithms, Computing and Systems
September 2021
139 pages
ISBN:9781450385084
DOI:10.1145/3490700
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 05 January 2022

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Author Tags

  1. Hybrid storage
  2. Neo4j
  3. RDF
  4. SPARQL
  5. TinkerPop

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