Abstract
Recommender systems are widely used to recommend the most appealing items to users. These recommendations can be generated by applying collaborative filtering methods. The low-rank matrix completion method is the state-of-the-art collaborative filtering method. In this work, we show that the skewed distribution of ratings in the user-item rating matrix of real-world datasets affects the accuracy of matrix-completion-based approaches. Also, we show that the number of ratings that an item or a user has positively correlates with the ability of low-rank matrix-completion-based approaches to predict the ratings for the item or the user accurately. Furthermore, we use these insights to develop four matrix completion-based approaches, i.e., Frequency Adaptive Rating Prediction (FARP), Truncated Matrix Factorization (TMF), Truncated Matrix Factorization with Dropout (TMF + Dropout) and Inverse Frequency Weighted Matrix Factorization (IFWMF), that outperforms traditional matrix-completion-based approaches for the users and the items with few ratings in the user-item rating matrix.
Original language | English (US) |
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Title of host publication | The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019 |
Publisher | Association for Computing Machinery, Inc |
Pages | 3223-3229 |
Number of pages | 7 |
ISBN (Electronic) | 9781450366748 |
DOIs | |
State | Published - May 13 2019 |
Event | 2019 World Wide Web Conference, WWW 2019 - San Francisco, United States Duration: May 13 2019 → May 17 2019 |
Publication series
Name | The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019 |
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Conference
Conference | 2019 World Wide Web Conference, WWW 2019 |
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Country/Territory | United States |
City | San Francisco |
Period | 5/13/19 → 5/17/19 |
Bibliographical note
Publisher Copyright:© 2019 IW3C2 (International World Wide Web Conference Committee), published under Creative Commons CC-BY 4.0 License.
Keywords
- Collaborative filtering
- Matrix completion
- Matrix factorization
- Recommender systems