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The Frontiers of Society, Science and Technology, 2021, 3(1); doi: 10.25236/FSST.2021.030119.

Combining User-Genre Preference Information with Neural Collaborative Filtering


Zehao Jiang1, Yi Yi2, Xingyu Zhu3,

Corresponding Author:
Xingyu Zhu

1School of Computer Science, Harbin Institute of Technology, Harbin, 150001, China

2School of Mathematical Science, Shanghai Jiao Tong University, Shanghai, 200240, China

3Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China


In this paper, the user-genre preference information is introduced into collaborative filtering (CF) to deal with the sparsity which CF suffers from. This work classifies items by genre information, it applies neural collaborative filtering model in each category and combines all models together to get a final prediction. These experiments in the work are conducted on well-known dataset in which hit ratio and Normalized Discounted Cumulative Gain (NDCG) are introduced into the evaluation. It indicates that our model has fast performance growth and good results.


Genre Information, Collaborative Filtering, Recommendation System, Neural Network

Cite This Paper

Zehao Jiang, Yi Yi, Xingyu Zhu. Combining User-Genre Preference Information with Neural Collaborative Filtering. The Frontiers of Society, Science and Technology (2021) Vol. 3, Issue 1: 125-129. https://doi.org/10.25236/FSST.2021.030119.


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