Name
Abstract | ||
|---|---|---|
We propose a method that combines terminological decision trees and the Dempster-Shafer Theory, to support tasks like ontology completion. The goal is to build a predictive model that can cope with the epistemological uncertainty due to the Open World Assumption when reasoning with Web ontologies. With such models not only one can predict new (non derivable) assertions for completing the ontology but by assessing the quality of the induced axioms. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-08795-5_5 | Communications in Computer and Information Science |
Field | DocType | Volume |
Data science,Ontology (information science),Ontology,Decision tree,Axiom,Computer science,Open-world assumption,Natural language processing,Artificial intelligence,Evidence-based practice | Conference | 442 |
ISSN | Citations | PageRank |
1865-0929 | 6 | 0.49 |
References | Authors | |
6 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Giuseppe Rizzo | 1 | 349 | 37.75 |
| Claudia D'Amato | 2 | 733 | 57.03 |
| Nicola Fanizzi | 3 | 1124 | 90.54 |
| Floriana Esposito | 4 | 2434 | 277.96 |