1 research outputs found
A fuzzy similarity based approach for intelligent web based e-learning
In this paper, an intelligent system for web based e-Learning is proposed
which analyzes students knowledge capacity by applying clustering technique.
This system uses fuzzy logic and k-means clustering algorithm to arrange the
documents according to the level of their performance. Moreover, a new domain
ontology alignment technique is proposed that uses contextual information of
the knowledge sources from the e-Learning domain for effective decision making.
The proposed ontology alignment method has been empirically tested in an
e-Learning environment and the experimental results show that the proposed
method performs better than the existing methods in terms of precision and
recall. The salient contributions of this paper are the use of Jaccard
Similarity, fuzzy approach for ontology alignment and K-Means clustering
algorithm for decision making using decision rules for providing intelligent
e-Learning.Comment: 6 pages, 7 figures and 1 tabl