Name
Abstract | ||
|---|---|---|
Ontologies constitute an approach for knowledge represen- tation that can be shared establishing a shared vocabulary for dierent applications and are also the backbone of the Semantic Web. Thus a fast and ecient ontology development is a requirement for the suc- cess of many knowledge based systems and for the Semantic Web itself. However, ontology development is a dicult and time consuming task. Ontology learning is an approach for the problem of knowledge acquisi- tion bottleneck that aims at reducing the cost of ontology construction through the development of automatic methods for the extraction of knowledge about a specific domain and its representation in an ontol- ogy like structure. This paper provides a discussion on existing ontology learning techniques and the state of the art of the field. |
Year | Venue | Keywords |
|---|---|---|
2008 | WONTO | ontologies,knowl- edge acquisition,ontology learning,machine learning,semantic web,knowledge based system |
Field | DocType | Citations |
Ontology (information science),Ontology-based data integration,Process ontology,Information retrieval,Open Biomedical Ontologies,Computer science,Ontology Inference Layer,Suggested Upper Merged Ontology,Upper ontology,Ontology learning | Conference | 32 |
PageRank | References | Authors |
1.65 | 25 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lucas Drumond | 1 | 395 | 24.27 |
| Rosario Girardi | 2 | 120 | 11.12 |