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).
|Publication date||Jul 2014|
|Publication status||Published - Jul 2014|
|Event||The 14th IEEE International Conference on Advanced Learning Technologies : Advanced Technologies for Supporting Open Access to Formal and Informal Learning - Athens, Greece|
Duration: 7 Jul 2014 → 9 Jul 2014
|Conference||The 14th IEEE International Conference on Advanced Learning Technologies|
|Period||07/07/2014 → 09/07/2014|
- Knowledge Representation; Fuzzy Description Logic; OWL2 Ontologies; Semantic Web; Intelligent Educa- tional System; E-Learning