International Journal of
Information and Education Technology

Abstract

To solve the problem that the distance education inevitably produced the “isolated” learners, the learners with the same interest are organized into the same community for collaborative learning. In view of neglecting the semantic relevance between terms of the traditional vector space model, the vector space model based on ontology is proposed to calculate the learner's interest eigenvector, and the corresponding explicit express can be obtained according to the recessive expression, which improves the accuracy of the interest similarity comparison. At the same time, a self-organization algorithm based on the similarity match-degree and matching concentration of learner's interest for the learning community is put forward. Great dimensions would take place with the ontology to construct vector space, thus Concept Indexing method is adopted to reasonably reduce the dimensionality of interest characteristic matrix so that greatly reduces the computational complexity. Finally, an experimental analysis of online education cases indicates that the algorithm has high efficiency and good extensibility.