Abstract
Knowledge representation models based on Fuzzy Description Logics (DLs) can provide a foundation for reasoning in intelligent learning environments. While basic DLs are suitable for expressing crisp concepts and binary relationships, Fuzzy DLs are capable of processing degrees of truth/completeness about vague or imprecise information. This paper tackles the issue of representing fuzzy classes using OWL2 in a dataset describing Performance Assessment Results of Students (PARS).
| Originalsprog | Engelsk |
|---|---|
| Titel | IEEE 14th International Conference on Advanced Learning Technologies |
| Publikationsdato | jul. 2014 |
| Status | Udgivet - jul. 2014 |
| Begivenhed | The 14th IEEE International Conference on Advanced Learning Technologies : Advanced Technologies for Supporting Open Access to Formal and Informal Learning - Athens, Grækenland Varighed: 7 jul. 2014 → 9 jul. 2014 |
Konference
| Konference | The 14th IEEE International Conference on Advanced Learning Technologies |
|---|---|
| Land/Område | Grækenland |
| By | Athens |
| Periode | 07/07/2014 → 09/07/2014 |