Goal-based framework for multi-user personalized similaritiesin e-learning scenarios
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: co...
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my.utm.597692022-02-17T06:55:49Z http://eprints.utm.my/id/eprint/59769/ Goal-based framework for multi-user personalized similaritiesin e-learning scenarios Chughtai, Muhammad Waseem Ghani, Imran Selamat, Ali Jeong, Seung Ryul QA75 Electronic computers. Computer science 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. IGI Global 2014-01 Article PeerReviewed Chughtai, Muhammad Waseem and Ghani, Imran and Selamat, Ali and Jeong, Seung Ryul (2014) Goal-based framework for multi-user personalized similaritiesin e-learning scenarios. International Journal of Technology and Educational Marketing, 4 (1). pp. 1-14. ISSN 2155-5605 http://dx.doi.org/10.4018/ijtem.2014010101 DOI:10.4018/ijtem.2014010101 |
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QA75 Electronic computers. Computer science Chughtai, Muhammad Waseem Ghani, Imran Selamat, Ali Jeong, Seung Ryul Goal-based framework for multi-user personalized similaritiesin e-learning scenarios |
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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. |
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Article |
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Chughtai, Muhammad Waseem Ghani, Imran Selamat, Ali Jeong, Seung Ryul |
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Chughtai, Muhammad Waseem Ghani, Imran Selamat, Ali Jeong, Seung Ryul |
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Chughtai, Muhammad Waseem |
title |
Goal-based framework for multi-user personalized similaritiesin e-learning scenarios |
title_short |
Goal-based framework for multi-user personalized similaritiesin e-learning scenarios |
title_full |
Goal-based framework for multi-user personalized similaritiesin e-learning scenarios |
title_fullStr |
Goal-based framework for multi-user personalized similaritiesin e-learning scenarios |
title_full_unstemmed |
Goal-based framework for multi-user personalized similaritiesin e-learning scenarios |
title_sort |
goal-based framework for multi-user personalized similaritiesin e-learning scenarios |
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IGI Global |
publishDate |
2014 |
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http://eprints.utm.my/id/eprint/59769/ http://dx.doi.org/10.4018/ijtem.2014010101 |
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1725972654215659520 |
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13.18916 |