Fuzzy folksonomy-based index creation for e-Learning content retrieval on cloud computing environments

Due to the trend of individualization and adaptation of e-Learning, more and more SCORM-compliant teaching materials are developed by institutes and individuals in different sites. Also, cloud computing environments are emerging as powerful infrastructures to support e-Learning applications. Therefore, how to rapidly retrieve SCORM-compliant documents on cloud computing environments has become an important issue. Creating an index from folksonomies has been investigated in previous researches; however, the involved uncertainty has not been addressed. This paper focuses on the fuzzy index creation problem for learning content retrieval. A bottom-up approach to constructing the fuzzy index is proposed. The index creation method has been implemented, and a synthetic learning object repository has been built on a Hadoop cloud platform to evaluate the proposed approach. Experimental results show that this method can increase precision of retrieval.

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