A Simple and Effective Combination of User-Based and Item-Based Recommendation Methods


Se-Chang Oh, Min Choi, Journal of Information Processing Systems Vol. 15, No. 1, pp. 127-136, Feb. 2019  

https://doi.org/10.3745/JIPS.01.0036
Keywords: Collaborative Filtering, Electronic commerce, Recommender System, Sparsity
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Abstract

User-based and item-based approaches have been developed as the solutions of the movie recommendation problem. However, the user-based approach is faced with the problem of sparsity, and the item-based approach is faced with the problem of not reflecting users’ preferences. In order to solve these problems, there is a research on the combination of the two methods using the concept of similarity. In reality, it is not free from the problem of sparsity, since it has a lot of parameters to be calculated. In this study, we propose a combining method that simplifies the combination equation of prior study. This method is relatively free from the problem of sparsity, since it has less parameters to be calculated. Thus, it can get more accurate results by reflecting the users rating to calculate the parameters. It is very fast to predict new movie ratings as well. In experiments for the proposed method, the initial error is large, but the performance gets quickly stabilized after. In addition, it showed about 6% lower average error rate than the existing method using similarity.


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Cite this article
[APA Style]
Oh, S. & Choi, M. (2019). A Simple and Effective Combination of User-Based and Item-Based Recommendation Methods. Journal of Information Processing Systems, 15(1), 127-136. DOI: 10.3745/JIPS.01.0036.

[IEEE Style]
S. Oh and M. Choi, "A Simple and Effective Combination of User-Based and Item-Based Recommendation Methods," Journal of Information Processing Systems, vol. 15, no. 1, pp. 127-136, 2019. DOI: 10.3745/JIPS.01.0036.

[ACM Style]
Se-Chang Oh and Min Choi. 2019. A Simple and Effective Combination of User-Based and Item-Based Recommendation Methods. Journal of Information Processing Systems, 15, 1, (2019), 127-136. DOI: 10.3745/JIPS.01.0036.