Lian Kei Soo

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This paper proposed the ontology based personalized recommendation model for learning objects in order to increase the reusability of the learning objects. The model will assist the users to select the “best fit” learning objects by referring to their preference history. The search keywords inputted by the users will be processed and the semantic similar(More)
This paper proposes a revised architecture for Service Oriented Architecture (SOA) e-learning system to enhance the reusability of the Learning Objects (LOs) by providing a personalized recommendation model (searching and ranking processes) which is having a shorter processing time, comparing with other approaches. The model counts the similarity degree(More)
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