Name
Abstract | ||
|---|---|---|
We report on a study of our custom Hootation software for the purposes of assessing its ability to produce clear and accurate natural language phrases from axioms embedded in three biomedical ontologies. Using multiple domain experts and three discrete rating scales, we evaluated the tool on clarity of the natural language produced, fidelity of the natural language produced from the ontology to the axiom, and the fidelity of the domain knowledge represented by the axioms. Results show that Hootation provided relatively clear natural language equivalents for a select set of OWL axioms, although the clarity of statements hinges on the accuracy and representation of axioms in the ontology. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.3233/978-1-61499-830-3-838 | Studies in Health Technology and Informatics |
Keywords | DocType | Volume |
Natural Language Processing,Biomedical Ontologies,Knowledge Management | Conference | 245 |
ISSN | Citations | PageRank |
0926-9630 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Muhammad Amith | 1 | 22 | 9.01 |
| Frank J Manion | 2 | 0 | 0.34 |
| Marcelline R Harris | 3 | 0 | 0.34 |
| Zhang Yaoyun | 4 | 56 | 14.30 |
| Hua Xu | 5 | 650 | 69.76 |
| Cui Tao | 6 | 269 | 37.21 |