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A Gaussian Process Model for Knowledge Propagation in Web Ontologies

Minervini, P; Damato, C; Fanizzi, N; Esposito, F; (2015) A Gaussian Process Model for Knowledge Propagation in Web Ontologies. In: (Proceedings) 2014 IEEE International Conference on Data Mining (ICDM),. (pp. pp. 929-934). IEEE Green open access

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Abstract

We consider the problem of predicting missing class-memberships and property values of individual resources in Web ontologies. We first identify which relations tend to link similar individuals by means of a finite-set Gaussian Process regression model, and then efficiently propagate knowledge about individuals across their relations. Our experimental evaluation demonstrates the effectiveness of the proposed method.

Type: Proceedings paper
Title: A Gaussian Process Model for Knowledge Propagation in Web Ontologies
Event: 2014 IEEE International Conference on Data Mining (ICDM),
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/ICDM.2014.83
Publisher version: https://doi.org/10.1109/ICDM.2014.83
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Ontologies, Kernel, Training, Portals, Symmetric matrices, Gaussian processes, Labeling
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10043032
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