File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Optimizing subgraph matching over distributed knowledge graphs using partial evaluation

TitleOptimizing subgraph matching over distributed knowledge graphs using partial evaluation
Authors
KeywordsPartial evaluation
RDF graph
Subgraph matching
Issue Date2023
Citation
World Wide Web, 2023, v. 26, n. 2, p. 751-771 How to Cite?
AbstractThe partial evaluation and assembly framework has recently been applied for processing subgraph matching queries over large-scale knowledge graphs in the distributed environment. The framework is implemented on the master-slave architecture, endowed with outstanding scalability. However, there are two drawbacks of partial evaluation: if the volume of intermediate results is large, a large number of repeated partial matches will be generated; and the assembly computation handled by the master would be a bottleneck. In this paper, we propose an optimal partial evaluation algorithm and a filter method to reduce partial matches by exploring the computing characteristics of partial evaluation and assembly framework. (1) An index structure named inner boundary node index (IBN-Index) is constructed to prune for graph exploration to improve the searching efficiency of the partial evaluation phase. (2) The boundary characteristics of local partial matches are utilized to construct a boundary node index (BN-Index) to reduce the number of local partial matches. (3) The experimental results over benchmark datasets show that our approach outperforms the state-of-the-art methods.
Persistent Identifierhttp://hdl.handle.net/10722/330832
ISSN
2023 Impact Factor: 2.7
2023 SCImago Journal Rankings: 1.122
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorSong, Yanyan-
dc.contributor.authorQin, Yuzhou-
dc.contributor.authorHao, Wenqi-
dc.contributor.authorLiu, Pengkai-
dc.contributor.authorLi, Jianxin-
dc.contributor.authorChoudhury, Farhana Murtaza-
dc.contributor.authorWang, Xin-
dc.contributor.authorZhang, Qingpeng-
dc.date.accessioned2023-09-05T12:15:02Z-
dc.date.available2023-09-05T12:15:02Z-
dc.date.issued2023-
dc.identifier.citationWorld Wide Web, 2023, v. 26, n. 2, p. 751-771-
dc.identifier.issn1386-145X-
dc.identifier.urihttp://hdl.handle.net/10722/330832-
dc.description.abstractThe partial evaluation and assembly framework has recently been applied for processing subgraph matching queries over large-scale knowledge graphs in the distributed environment. The framework is implemented on the master-slave architecture, endowed with outstanding scalability. However, there are two drawbacks of partial evaluation: if the volume of intermediate results is large, a large number of repeated partial matches will be generated; and the assembly computation handled by the master would be a bottleneck. In this paper, we propose an optimal partial evaluation algorithm and a filter method to reduce partial matches by exploring the computing characteristics of partial evaluation and assembly framework. (1) An index structure named inner boundary node index (IBN-Index) is constructed to prune for graph exploration to improve the searching efficiency of the partial evaluation phase. (2) The boundary characteristics of local partial matches are utilized to construct a boundary node index (BN-Index) to reduce the number of local partial matches. (3) The experimental results over benchmark datasets show that our approach outperforms the state-of-the-art methods.-
dc.languageeng-
dc.relation.ispartofWorld Wide Web-
dc.subjectPartial evaluation-
dc.subjectRDF graph-
dc.subjectSubgraph matching-
dc.titleOptimizing subgraph matching over distributed knowledge graphs using partial evaluation-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/s11280-022-01075-6-
dc.identifier.scopuseid_2-s2.0-85133613557-
dc.identifier.volume26-
dc.identifier.issue2-
dc.identifier.spage751-
dc.identifier.epage771-
dc.identifier.eissn1573-1413-
dc.identifier.isiWOS:000824974800005-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats