Normalization-based neighborhood model for cold start problem in recommendation system
Existing approaches for Recommendation Systems (RS) are mainly based on users’ past knowledge and the more popular techniques such as the neighborhood models focus on finding similar users in making recommendations. The cold start problem is due to inaccurate recommendations given to new users becau...
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Zarqa University
2020
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Online Access: | http://psasir.upm.edu.my/id/eprint/86921/1/Normalization-based%20neighborhood.pdf http://psasir.upm.edu.my/id/eprint/86921/ https://iajit.org/portal/index.php/archive/volume-17-2020/may-2020-no-3/item/180-normalization-based-neighborhood-model-for-cold-start-problem-in-recommendation-system |
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my.upm.eprints.869212022-01-05T08:35:27Z http://psasir.upm.edu.my/id/eprint/86921/ Normalization-based neighborhood model for cold start problem in recommendation system Zahid, Aafaq Mohd Sharef, Nurfadhlina Mustapha, Aida Existing approaches for Recommendation Systems (RS) are mainly based on users’ past knowledge and the more popular techniques such as the neighborhood models focus on finding similar users in making recommendations. The cold start problem is due to inaccurate recommendations given to new users because of lack of past data related to those users. To deal with such cases where prior information on the new user is not available, this paper proposes a normalization technique to model user involvement for cold start problem or user likings based on the details of items used in the neighborhood models. The proposed normalization technique was evaluated using two datasets namely MovieLens and GroupLens. The results showed that the proposed technique is able to improve the accuracy of the neighborhood model, which in turn increases the accuracy of an RS. Zarqa University 2020-05 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/86921/1/Normalization-based%20neighborhood.pdf Zahid, Aafaq and Mohd Sharef, Nurfadhlina and Mustapha, Aida (2020) Normalization-based neighborhood model for cold start problem in recommendation system. International Arab Journal of Information Technology, 17 (3). 281 - 289. ISSN 2309-4524 https://iajit.org/portal/index.php/archive/volume-17-2020/may-2020-no-3/item/180-normalization-based-neighborhood-model-for-cold-start-problem-in-recommendation-system 10.34028/iajit/17/3/1 |
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Existing approaches for Recommendation Systems (RS) are mainly based on users’ past knowledge and the more popular techniques such as the neighborhood models focus on finding similar users in making recommendations. The cold start problem is due to inaccurate recommendations given to new users because of lack of past data related to those users. To deal with such cases where prior information on the new user is not available, this paper proposes a normalization technique to model user involvement for cold start problem or user likings based on the details of items used in the neighborhood models. The proposed normalization technique was evaluated using two datasets namely MovieLens and GroupLens. The results showed that the proposed technique is able to improve the accuracy of the neighborhood model, which in turn increases the accuracy of an RS. |
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Article |
author |
Zahid, Aafaq Mohd Sharef, Nurfadhlina Mustapha, Aida |
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Zahid, Aafaq Mohd Sharef, Nurfadhlina Mustapha, Aida Normalization-based neighborhood model for cold start problem in recommendation system |
author_facet |
Zahid, Aafaq Mohd Sharef, Nurfadhlina Mustapha, Aida |
author_sort |
Zahid, Aafaq |
title |
Normalization-based neighborhood model for cold start problem in recommendation system |
title_short |
Normalization-based neighborhood model for cold start problem in recommendation system |
title_full |
Normalization-based neighborhood model for cold start problem in recommendation system |
title_fullStr |
Normalization-based neighborhood model for cold start problem in recommendation system |
title_full_unstemmed |
Normalization-based neighborhood model for cold start problem in recommendation system |
title_sort |
normalization-based neighborhood model for cold start problem in recommendation system |
publisher |
Zarqa University |
publishDate |
2020 |
url |
http://psasir.upm.edu.my/id/eprint/86921/1/Normalization-based%20neighborhood.pdf http://psasir.upm.edu.my/id/eprint/86921/ https://iajit.org/portal/index.php/archive/volume-17-2020/may-2020-no-3/item/180-normalization-based-neighborhood-model-for-cold-start-problem-in-recommendation-system |
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13.160551 |