Name
Abstract | ||
|---|---|---|
Ontologies, such as UMLS and WordNet, are generally very large, and are normally the source of more specialised and smaller ontologies tailored for a certain application. It is natural that the source ontologies be multiple large ontologies, each of which is extracted, and then merged to create a smaller and tailored ontology for a specific domain. Therefore, extracting sub-ontologies as well as merging them is a primary process. In this paper, we propose sub-ontology extraction and merging, whereby multiple sub-ontologies are extracted from various source ontologies and then these extracted sub-ontologies are merged to form a complete ontology to be used by the user. We use the maximum extraction method to facilitate this. A walkthrough case study using the UMLS meta-thesaurus ontology is also presented. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1504/IJWGS.2014.060262 | IJWGS |
Keywords | Field | DocType |
merging sub-ontologies,maximum extraction method,various source ontology,smaller ontology,tailored ontology,sub-ontology extraction,multiple large ontology,multiple sub-ontologies,umls meta-thesaurus ontology,source ontology,complete ontology,ontology | Ontology merging,Ontology (information science),Data mining,Ontology-based data integration,Information retrieval,Process ontology,Computer science,Open Biomedical Ontologies,IDEF5,Suggested Upper Merged Ontology,Upper ontology | Journal |
Volume | Issue | Citations |
10 | 2/3 | 0 |
PageRank | References | Authors |
0.34 | 12 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrew Flahive | 1 | 159 | 13.87 |
| David Taniar | 2 | 1702 | 162.18 |
| J. Wenny Rahayu | 3 | 1275 | 106.72 |