Relational Collaborative Topic Regression for Recommender Systems

By Hao Wang, Wu-Jun Li. 2015

66 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Probabilistic & Bayesian Methods, Recommender 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. Dit-Yan Yeung
2. Hao Wang
3. Naiyan Wang
4. Yu Zhang
5. Qiang Yang
6. Xing Xie
7. Yu Zhang
8. Yongfeng Zhang

In Information Systems

1. Dit-Yan Yeung
2. Hao Wang
3. Naiyan Wang
4. Xing Xie
5. Yongfeng Zhang
6. Xu Chen
7. Fuzheng Zhang
8. Hongwei Wang

In Probabilistic & Bayesian Methods

1. Dit-Yan Yeung
2. Hao Wang
3. Naiyan Wang

In Recommender Systems

1. Dit-Yan Yeung
2. Hao Wang
3. Naiyan Wang
4. Xingjian Shi

Citations in the corpus

• Collaborative Deep Learning for Recommender Systems (2014, methodology): “For each dataset, similar to [35, 36], we randomly select P items associated with each user to form the training set and use all the rest of the dataset as the test set.”
• Towards Bayesian Deep Learning: A Survey (2016, methodology): “This model is then further extended to incorporate social information [44], [57], [58].”
• A Survey on Bayesian Deep Learning (2016, unknown): “This model is then further extended to incorporate social information [89, 115, 116].”