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dc.contributor.authorWang, X
dc.contributor.authorChai, L
dc.contributor.authorXu, Q
dc.contributor.authorYang, Y
dc.contributor.authorLi, J
dc.contributor.authorWang, J
dc.contributor.authorChai, Y
dc.date.accessioned2019-07-11T01:00:17Z
dc.date.available2019-07-11T01:00:17Z
dc.date.issued2019
dc.identifier.issn2364-1185
dc.identifier.doi10.1007/s41019-019-0090-z
dc.identifier.urihttp://hdl.handle.net/10072/386262
dc.description.abstractWith the popularity of knowledge graphs growing rapidly, large amounts of RDF graphs have been released, which raises the need for addressing the challenge of distributed subgraph matching queries. In this paper, we propose an efficient distributed method to answer subgraph matching queries on big RDF graphs using MapReduce. In our method, query graphs are decomposed into a set of stars that utilize the semantic and structural information embedded RDF graphs as heuristics. Two optimization techniques are proposed to further improve the efficiency of our algorithms. One algorithm, called RDF property filtering, filters out invalid input data to reduce intermediate results; the other is to improve the query performance by postponing the Cartesian product operations. The extensive experiments on both synthetic and real-world datasets show that our method outperforms the close competitors S2X and SHARD by an order of magnitude on average.
dc.description.peerreviewedYes
dc.publisherSpringer
dc.relation.ispartofpagefrom24
dc.relation.ispartofpageto43
dc.relation.ispartofissue1
dc.relation.ispartofjournalData Science and Engineering
dc.relation.ispartofvolume4
dc.subject.fieldofresearchCommunications Technologies
dc.subject.fieldofresearchcode1005
dc.titleEfficient Subgraph Matching on Large RDF Graphs Using MapReduce
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
dcterms.licensehttp://creat iveco mmons .org/licen ses/by/4.0/
dc.description.versionPublished
gro.rights.copyright© 2019 The Authors. This article is distributed under the terms of the Crea-tive Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
gro.hasfulltextFull Text
gro.griffith.authorWang, John


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