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
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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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