Title: Fuzzy-MCS algorithm-based ontology generation for e-assessment

Authors: A. Santhanavijayan; S.R. Balasundaram

Addresses: Department of Computer Science and Engineering, National Institute of Technology, Tiruchirappalli, India ' Department of Computer Applications, National Institute of Technology, Tiruchirappalli, India

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.

Keywords: ontologies; MCS algorithm; fuzzy; e-learning.

DOI: 10.1504/IJBIDM.2019.099959

International Journal of Business Intelligence and Data Mining, 2019 Vol.14 No.4, pp.458 - 472

Received: 29 Nov 2016
Accepted: 23 Feb 2017
Published online: 03 Jun 2019 *

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