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Goal-Based Framework for Multi-User Personalized Similarities in e-Learning Scenarios


  • M. Waseem Chughtai

    (Software Engineering Department, Faculty of Computing, Universiti Teknologi Malaysia (UTM), Johor Bahru, Johor, Malaysia)

  • Imran Ghani

    (Software Engineering Department, Faculty of Computing, Universiti Teknologi Malaysia (UTM), Johor Bahru, Johor, Malaysia)

  • Ali Selamat

    (Software Engineering Department, Faculty of Computing, Universiti Teknologi Malaysia (UTM), Johor Bahru, Johor, Malaysia)

  • Seung Ryul Jeong

    (School of Business IT, Kookmin University, Seoul, South Korea)


Web-based learning or e-Learning in contrast to traditional education systems offer a lot of benefits. This article presents the Goal-based Framework for providing personalized similarities between multi users profile preferences in formal e-Learning scenarios. It consists of two main approaches: content-based filtering and collaborative filtering. Because only traditional content-based filtering is not sufficient to generate the recommendations for new-users, therefore, the proposed work hybridized multi user's collaborative filtering functionalities with personalized content-based profile preferences filtering. The main purpose of this proposed work is to (a) overcome the user-based cold-start profile recommendations and (b) improve the recommendations accuracy for new-users in formal e-learning recommendation systems. The experimental has been done by using the famous ‘MovieLens' dataset with 15.86% density of the user-item matrix with respect to ratings, while the evaluation of experimental results have been performed with precision mean and recall mean to test the effectiveness of Goal-based personalized recommendation framework. The Experimental result Precision: 81.90% and Recall: 86.56% show that the proposed framework goals performed well for the improvement of user-based cold-start issue as well as for content-based profile recommendations, using multi users personalized collaborative similarities, in formal e-Learning scenarios effectively.

Suggested Citation

  • M. Waseem Chughtai & Imran Ghani & Ali Selamat & Seung Ryul Jeong, 2014. "Goal-Based Framework for Multi-User Personalized Similarities in e-Learning Scenarios," International Journal of Technology and Educational Marketing (IJTEM), IGI Global, vol. 4(1), pages 1-14, January.
  • Handle: RePEc:igg:jtem00:v:4:y:2014:i:1:p:1-14

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