A push strategy for delivering of Learning Objects using meta data based association analysis (FP-Tree)

摘要

Learning Materials are structured as Learning Objects and are available in Learning Object Repository(LOR) which are used in various courses of an Elearning environment. Learning Management System aggregates these objects found in LOR, provides an infrastructure and platform through which learning content is delivered and managed. Adaptation, personalization, usage statistics are some of the LMS functionality. But due to the exponential availability of Learning Objects, it leads to increase in difficulty to find the right resource to the user based on the context of learning or his/her preferences. When we search through keywords it results in huge quantity of information being displayed. In this paper we are considering the Search patterns of the users stored in search logs and based on it association rules are generated using Frequent Pattern Tree. We can generate a list of Frequent learning objects using frequent item set mining approach FP-Tree, so that a reduced, appropriate and relevant objects can be delivered to the users.