Name
Abstract | ||
|---|---|---|
In this paper we present an approach for the automatic identification of relations in ontologies of restricted domain. We use the evidence found in a corpus associated to the same domain of the ontology for determining the validity of the ontological relations. Our approach employs formal concept analysis, a method used for the analysis of data, but in this case used for relations discovery in a corpus of restricted domain. The approach uses two variants for filling the incidence matrix that this method employs. The formal concepts are used for evaluating the ontological relations of two ontologies. The performance obtained was about 96﾿for taxonomic relations and 100﾿% for non-taxonomic relations, in the first ontology. In the second it was about 92﾿% for taxonomic relations and 98﾿% for non-taxonomic relations. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-19264-2_23 | MCPR |
Keywords | Field | DocType |
Formal concept analysis, Ontology, Semantic relations | Ontology (information science),Ontology,Data analysis,Computer science,Natural language processing,Artificial intelligence,Formal concept analysis,Incidence matrix | Conference |
Volume | ISSN | Citations |
9116 | 0302-9743 | 1 |
PageRank | References | Authors |
0.37 | 4 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mireya Tovar | 1 | 31 | 15.59 |
| David Pinto | 2 | 280 | 35.77 |
| Azucena Montes Rendón | 3 | 36 | 5.45 |
| Juan Gabriel González Serna | 4 | 1 | 0.37 |
| Darnes Vilariño Ayala | 5 | 21 | 10.84 |