Name
Abstract | ||
|---|---|---|
In this paper we present an approach for the evaluation of taxonomic relations of restricted domain ontologies. We use the evidence found in corpora associated to the ontology domain for determining the validity of the taxonomic relations. Our approach employs lexico-syntactic patterns for evaluating taxonomic relations in which the concepts are totally different, and it uses a particular technique based on subsumption for those relations in which one concept is completely included in the other one. The integration of these two techniques has allowed to automatically evaluate taxonomic relations for two ontologies of restricted domain. The performance obtained was about 70% for one ontology of the e-learning domain, whereas we obtained around 88% for the ontology associated to the artificial intelligence domain. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-07491-7_34 | PATTERN RECOGNITION, MCPR 2014 |
Keywords | Field | DocType |
Lexico-syntactic patterns, Ontology evaluation, Taxonomic relations | Ontology (information science),Data mining,Ontology,Computer science,Artificial intelligence,Lexico,Natural language processing,Syntax,Machine learning | Conference |
Volume | ISSN | Citations |
8495 | 0302-9743 | 2 |
PageRank | References | Authors |
0.45 | 16 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mireya Tovar | 1 | 31 | 15.59 |
| David Pinto | 2 | 280 | 35.77 |
| Azucena Montes Rendón | 3 | 36 | 5.45 |
| Gabriel González Serna | 4 | 2 | 1.12 |
| Darnes Vilariño Ayala | 5 | 21 | 10.84 |
| Beatriz Beltrán | 6 | 12 | 11.33 |