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DOI: 10.14569/IJACSA.2017.081105
PDF

User based Recommender Systems using Implicative Rating Measure

Author 1: Lan Phuong Phan
Author 2: Hung Huu Huynh
Author 3: Hiep Xuan Huynh

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 11, 2017.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: This paper proposes the implicative rating measure developed on the typicality measure. The paper also proposes a new recommendation model presenting the top N items to the active users. The proposed model is based on the user-based collaborative filtering approach using the implicative intensity measure to find the nearest neighbors of the active users, and the proposed measure to predict users’ ratings for items. The model is evaluated on two datasets MovieLens and CourseRegistration, and compared to some existing models such as: the item based collaborative filtering model using the Jaccard measure, the user based collaborative filtering model using Jaccard measure, the popular items based model, the latent factor based model, and the association rule based model using the confidence measure. The experimental results show that the performance of the proposed model is better when compared to other five models.

Keywords: Implicative rating measure; recommender system; user-based collaborative filtering

Lan Phuong Phan, Hung Huu Huynh and Hiep Xuan Huynh, “User based Recommender Systems using Implicative Rating Measure” International Journal of Advanced Computer Science and Applications(IJACSA), 8(11), 2017. http://dx.doi.org/10.14569/IJACSA.2017.081105

@article{Phan2017,
title = {User based Recommender Systems using Implicative Rating Measure},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.081105},
url = {http://dx.doi.org/10.14569/IJACSA.2017.081105},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {11},
author = {Lan Phuong Phan and Hung Huu Huynh and Hiep Xuan Huynh}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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