User based Recommender Systems using Implicative Rating Measure
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2017, Vol 8, Issue 11
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.
Authors and Affiliations
Lan Phuong Phan, Hung Huu Huynh, Hiep Xuan Huynh
Keywords
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- EP ID EP240420
- DOI 10.14569/IJACSA.2017.081105
- Views 108
- Downloads 0
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