A Fuzzy Knowledge Representation Model for Student Performance Assessment

Research output: Contribution to conference without publisher/journalPosterResearchpeer-review

2 Citations (Scopus)
182 Downloads (Pure)

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 languageEnglish
Publication dateJul 2014
Publication statusPublished - Jul 2014
EventThe 14th IEEE International Conference on Advanced Learning Technologies : Advanced Technologies for Supporting Open Access to Formal and Informal Learning - Athens, Greece
Duration: 7 Jul 20149 Jul 2014

Conference

ConferenceThe 14th IEEE International Conference on Advanced Learning Technologies
CountryGreece
CityAthens
Period07/07/201409/07/2014

Keywords

  • Knowledge Representation; Fuzzy Description Logic; OWL2 Ontologies; Semantic Web; Intelligent Educa- tional System; E-Learning

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