Name
Abstract | ||
|---|---|---|
The ability of a user to select an appropriate, high-quality domain ontology from a set of available options would be most useful in knowledge engineering and other intelligent applications. This capability, however, requires good quality assessment metrics as well as automated support when there is a large number of ontologies from which to make a selection. This research analyzes existing metrics for domain ontology evaluation and extends them to derive a Layered Ontology Metrics Suite based on semiotic theory. The metrics are implemented in a Domain Ontology Ranking System (DoORS) prototype, the purpose of which is to search an ontology library for specific terms to retrieve candidate domain ontologies and then assess their quality and suitability based upon the suite of metrics. The prototype system is compared to existing approaches to automated ontology quality ranking to illustrate the usefulness of the research. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.datak.2018.02.001 | Data & Knowledge Engineering |
Keywords | Field | DocType |
Domain ontology,Interoperability,Metrics,Ontology assessment,Ontology evaluation,Ranking,Ontology,Semiotics,Semiotic layers,Domain Ontology Ranking System | Ontology (information science),Ontology,Suite,Ranking,Information retrieval,Computer science,Knowledge engineering | Journal |
Volume | Issue | ISSN |
115 | 1 | 0169-023X |
Citations | PageRank | References |
0 | 0.34 | 42 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Melinda McDaniel | 1 | 2 | 1.73 |
| Veda C. Storey | 2 | 2796 | 542.19 |
| Vijayan Sugumaran | 3 | 975 | 92.17 |