Name
Title | ||
|---|---|---|
Approximate Classification of Semantically Annotated Web Resources Exploiting Pseudo-metrics Induced by Local Models |
Abstract | ||
|---|---|---|
We present a classification method, founded in the instance-based learning and the disjunctive version space approach, for performing approximate retrieval from knowledge bases expressed in Description Logics. The method supplies answers even if the knowledge base of reference is inconsistent or incomplete. Moreover, the method may also induce new knowledge that can be suggested to the knowledge engineer, thus making the ontology population task semi-automatic. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/WI-IAT.2009.116 | Web Intelligence |
Keywords | Field | DocType |
description logics,description logic,semantic web,fault tolerance,intelligent agent,knowledge base,ontologies,instance based learning,classification,knowledge engineering,knowledge based systems,neural networks | Data mining,Population,Ontology,Computer science,Semantic Web,Description logic,Artificial intelligence,Natural language processing,Knowledge base,Ontology (information science),Information retrieval,Knowledge-based systems,Knowledge engineering | Conference |
Volume | Citations | PageRank |
1 | 1 | 0.37 |
References | Authors | |
5 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Claudia D'Amato | 1 | 733 | 57.03 |
| Nicola Fanizzi | 2 | 1124 | 90.54 |
| Floriana Esposito | 3 | 2434 | 277.96 |
| Thomas Lukasiewicz | 4 | 2618 | 165.18 |