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Article: Distributed Subgraph Matching on Big Knowledge Graphs Using Pregel

TitleDistributed Subgraph Matching on Big Knowledge Graphs Using Pregel
Authors
Keywordsdistributed
knowledge graphs
Pregel
RDF
Subgraph matching
Issue Date2019
Citation
IEEE Access, 2019, v. 7, p. 116453-116464 How to Cite?
AbstractWith RDF becoming the de facto standard for representing knowledge graphs, it is indispensable to develop scalable subgraph matching algorithms over big RDF graphs stored in distributed clusters. In this paper, we propose a novel distributed subgraph matching method SP-Tree, using the Pregel model, to answer subgraph matching queries on big RDF graphs. In our method, the query graph is transformed to a variant spanning tree based on the shortest paths. Two optimization techniques are proposed to improve the efficiency of our algorithms. One employs RDF shapes to filter out local computations and messages passed, the other postpones the Cartesian product operations in the matching process to reduce intermediate results. The extensive experiments on both synthetic and real-world datasets show that our SP-Tree subgraph matching method outperforms the state-of-the-art methods by an order of magnitude.
Persistent Identifierhttp://hdl.handle.net/10722/330500
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorXu, Qiang-
dc.contributor.authorWang, Xin-
dc.contributor.authorLi, Jianxin-
dc.contributor.authorZhang, Qingpeng-
dc.contributor.authorChai, Lele-
dc.date.accessioned2023-09-05T12:11:14Z-
dc.date.available2023-09-05T12:11:14Z-
dc.date.issued2019-
dc.identifier.citationIEEE Access, 2019, v. 7, p. 116453-116464-
dc.identifier.urihttp://hdl.handle.net/10722/330500-
dc.description.abstractWith RDF becoming the de facto standard for representing knowledge graphs, it is indispensable to develop scalable subgraph matching algorithms over big RDF graphs stored in distributed clusters. In this paper, we propose a novel distributed subgraph matching method SP-Tree, using the Pregel model, to answer subgraph matching queries on big RDF graphs. In our method, the query graph is transformed to a variant spanning tree based on the shortest paths. Two optimization techniques are proposed to improve the efficiency of our algorithms. One employs RDF shapes to filter out local computations and messages passed, the other postpones the Cartesian product operations in the matching process to reduce intermediate results. The extensive experiments on both synthetic and real-world datasets show that our SP-Tree subgraph matching method outperforms the state-of-the-art methods by an order of magnitude.-
dc.languageeng-
dc.relation.ispartofIEEE Access-
dc.subjectdistributed-
dc.subjectknowledge graphs-
dc.subjectPregel-
dc.subjectRDF-
dc.subjectSubgraph matching-
dc.titleDistributed Subgraph Matching on Big Knowledge Graphs Using Pregel-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/ACCESS.2019.2936465-
dc.identifier.scopuseid_2-s2.0-85089888013-
dc.identifier.volume7-
dc.identifier.spage116453-
dc.identifier.epage116464-
dc.identifier.eissn2169-3536-
dc.identifier.isiWOS:000484233300004-

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