Mining the semantic web statistical learning for next generation knowledge bases

DOI10.1007/s10618-012-0253-2zbMath1235.68228DBLPjournals/datamine/RettingerLTdF12OpenAlexW200741916WikidataQ57240249 ScholiaQ57240249MaRDI QIDQ408710

Volker Tresp, Claudia D'amato, Nicola Fanizzi, Uta Lösch, Achim Rettinger

Publication date: 11 April 2012

Published in: Data Mining and Knowledge Discovery (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10618-012-0253-2

zbMATH Keywords

knowledge representationkernelsdescription logicsontologyRDFsemantic weblinked datasemantic similarityfirst-order probabilistic learningmultivariate predictionrelational graphical models

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Knowledge representation (68T30)

Related Items (3)

Approximate classification with web ontologies through evidential terminological trees and forests ⋮ Fuzzy OWL-Boost: learning fuzzy concept inclusions via real-valued boosting ⋮ Finding relational redescriptions

Uses Software

• ElemStatLearn
• swrl
• DL-learner
• BayesOWL

Cites Work

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