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).
| Original language | English |
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| Title of host publication | IEEE 14th International Conference on Advanced Learning Technologies |
| 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
| Conference | The 14th IEEE International Conference on Advanced Learning Technologies |
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| Country/Territory | Greece |
| City | Athens |
| Period | 07/07/2014 → 09/07/2014 |
Keywords
- Knowledge Representation; Fuzzy Description Logic; OWL2 Ontologies; Semantic Web; Intelligent Educa- tional System; E-Learning