article

Finding association rules in semantic web data

Authors:

Victoria Nebot and

Rafael BerlangaAuthors Info & Claims

Knowledge-Based Systems, Volume 25, Issue 1

Pages 51 - 62

https://doi.org/10.1016/j.knosys.2011.05.009

Published: 01 February 2012 Publication History

Abstract

The amount of ontologies and semantic annotations available on the Web is constantly growing. This new type of complex and heterogeneous graph-structured data raises new challenges for the data mining community. In this paper, we present a novel method for mining association rules from semantic instance data repositories expressed in RDF/(S) and OWL. We take advantage of the schema-level (i.e. Tbox) knowledge encoded in the ontology to derive appropriate transactions which will later feed traditional association rules algorithms. This process is guided by the analyst requirements, expressed in the form of query patterns. Initial experiments performed on semantic data of a biomedical application show the usefulness and efficiency of the approach.

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Martin TFuentes VValtchev PDiallo ALacroix RHong JBures MPark JCerny T(2022)Generalized graph pattern discovery in linked data with data properties and a domain ontologyProceedings of the 37th ACM/SIGAPP Symposium on Applied Computing10.1145/3477314.3507301(1890-1899)Online publication date: 25-Apr-2022
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Published In

cover image Knowledge-Based Systems

Knowledge-Based Systems Volume 25, Issue 1

February, 2012

88 pages

ISSN:0950-7051

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Copyright © Elsevier B.V. © 2011.

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Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 February 2012

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Hao SChai CLi GTang NWang NYu X(2023)HOFD: An Outdated Fact Detector for Knowledge BasesIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2023.324822335:10(10775-10789)Online publication date: 27-Feb-2023
https://dl.acm.org/doi/10.1109/TKDE.2023.3248223
Martin TFuentes VValtchev PDiallo ALacroix RHong JBures MPark JCerny T(2022)Generalized graph pattern discovery in linked data with data properties and a domain ontologyProceedings of the 37th ACM/SIGAPP Symposium on Applied Computing10.1145/3477314.3507301(1890-1899)Online publication date: 25-Apr-2022
https://dl.acm.org/doi/10.1145/3477314.3507301
Zeman VKliegr TSvátek V(2021)RDFRulesSemantic Web10.3233/SW-20041312:4(569-602)Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.3233/SW-200413
Bobed CMaillot PCellier PFerré S(2020)Data-driven assessment of structural evolution of RDF graphsSemantic Web10.3233/SW-20036811:5(831-853)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.3233/SW-200368
Glaser EMorain AGemmell JRaicu DHung CCerny TShin DBechini A(2020)Comparing automatically extracted topics from online suicidal ideation and the responses they invokeProceedings of the 35th Annual ACM Symposium on Applied Computing10.1145/3341105.3373902(1818-1825)Online publication date: 30-Mar-2020
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Maillot PBobed CHaddad HWainwright RChbeir R(2018)Measuring structural similarity between RDF graphsProceedings of the 33rd Annual ACM Symposium on Applied Computing10.1145/3167132.3167342(1960-1967)Online publication date: 9-Apr-2018
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Beretta VHarispe SRanwez SMougenot I(2018)Combining Truth Discovery and RDF Knowledge Bases to Their Mutual AdvantageThe Semantic Web – ISWC 201810.1007/978-3-030-00671-6_38(652-668)Online publication date: 8-Oct-2018
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Yu XMiao SLiu HHwang JWan WLu J(2017)Association Rule Mining of Personal Hobbies in Social NetworksInternational Journal of Web Services Research10.4018/IJWSR.201701010214:1(13-28)Online publication date: 1-Jan-2017
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