Name
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. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICDM.2014.83 | Data Mining |
Keywords | Field | DocType |
Gaussian processes,Internet,ontologies (artificial intelligence),regression analysis,Web ontologies,class-memberships,finite-set Gaussian process regression model,knowledge propagation,property values,gaussian process,semantic web,semi-supervised,transductive | Ontology (information science),Kernel (linear algebra),Kriging,Transduction (machine learning),Data mining,Computer science,Semantic Web,Symmetric matrix,Artificial intelligence,Gaussian process,Machine learning | Conference |
ISSN | Citations | PageRank |
1550-4786 | 2 | 0.37 |
References | Authors | |
7 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pasquale Minervini | 1 | 2 | 0.37 |
| Claudia D'Amato | 2 | 733 | 57.03 |
| Nicola Fanizzi | 3 | 2 | 0.37 |
| Floriana Esposito | 4 | 2434 | 277.96 |