Support vector machines for collaborative filtering

By Zhonghang Xia, Yulin Dong, Guangming Xing. 2006

56 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Miao Zhao
2. Hongwei Wang
3. Minyi Guo
4. Josep M. Pujol
5. Jiannong Cao
6. Alejandro Jaimes
7. Nuria Oliver
8. Jia Wang

In Computer Vision and Pattern Recognition

1. Jiannong Cao
2. Alejandro Jaimes
3. Nuria Oliver
4. Minyi Guo
5. Jia Wang
6. Miao Zhao
7. Xavier Amatriain
8. Hongwei Wang

In Information Systems

1. Miao Zhao
2. Hongwei Wang
3. Minyi Guo
4. Josep M. Pujol
5. Jiannong Cao
6. Alejandro Jaimes
7. Nuria Oliver
8. Jia Wang

Citations in the corpus

• Joint Topic-Semantic-aware Social Recommendation for Online Voting (2017, methodology): “In addition, various models are incorporated into collaborative filtering, such as Support Vector Machine [30], Restricted Boltzmann Machine [24], and Stacked Denoising Auto Encoder [27].”
• Data Mining Methods for Recommender Systems (2015, methodology): “Xia et al.[75] present different approaches to using SVM’s for RS in a CF setting.”
• Recommender Systems (2016, unknown): “For example, smoothing support vector machines [638] have been used to estimate the missing values in the user-item matrix in an iterative way.”