Name
Abstract | ||
|---|---|---|
Ontology development is a non-trivial task requiring expertise in the chosen ontological language. We propose a method for making the content of ontologies more transparent by presenting, through the use of natural language generation, naturalistic descriptions of ontology classes as textual paragraphs. The method has been implemented in a proof-of-concept system, OntoVerbal, that automatically generates paragraph-sized textual descriptions of ontological classes expressed in OWL. OntoVerbal has been applied to ontologies that can be loaded into Protege and been evaluated with SNOMED CT, showing that it provides coherent, well-structured and accurate textual descriptions of ontology classes. |
Year | Venue | Keywords |
|---|---|---|
2013 | INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS | ontology verbalisation, natural language generation, OWL, SNOMED CT |
Field | DocType | Volume |
Data mining,Ontology,Computer science,OWL-S,Natural language processing,Artificial intelligence,SNOMED CT,Ontology (information science),Ontology-based data integration,Process ontology,Information retrieval,Upper ontology,Ontology components | Journal | 4 |
Issue | ISSN | Citations |
6 | 2158-107X | 5 |
PageRank | References | Authors |
0.48 | 16 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shao Fen Liang | 1 | 33 | 4.53 |
| Donia Scott | 2 | 634 | 71.58 |
| Robert Stevens | 3 | 5538 | 499.01 |
| Alan Rector | 4 | 1489 | 161.78 |