Fuzzy-MCS algorithm-based ontology generation for e-assessment
by A. Santhanavijayan; S.R. Balasundaram
International Journal of Business Intelligence and Data Mining (IJBIDM), Vol. 14, No. 4, 2019

Abstract: Ontologies can lead to important improvements in the definition of a course's knowledge domain, in the generation of an adapted learning path, and in the assessment phase. This paper provides an initial discussion of the role of ontologies in the context of e-learning. Generally, automatic assessment is preferred over manual assessment to avoid bias errors, human errors and also conserves teacher's time. Evaluation through objective tests like multiple choice questions has gained a lot of importance in the e-assessment system. Here we have proposed an efficient ontology generation based on soft computing techniques in e-assessment for multiple choice questions. We have employed fuzzy logic incorporated with optimisation algorithm like modified cuckoo search algorithm. Here a set of rules are first designed for creating the ontology. The rules are generated using fuzzy logic and these rules are optimised in order to generate a better ontology structure.

Online publication date: Mon, 03-Jun-2019

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