Identifying and utilizing contextual data in hybrid recommender systems

By Alan Said. 2010

21 citations recorded by the source corpus.

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

1. Wu-Jun Li
2. Hao Wang
3. Dacheng Tao
4. Cheng Deng
5. Fumin Shen

In Information Systems

1. Hao Wang
2. Wu-Jun Li
3. Dit-Yan Yeung
4. Xing Xie

In Recommender Systems

1. Hao Wang
2. Wu-Jun Li
3. Dit-Yan Yeung
4. Naiyan Wang

Citations in the corpus

• Collaborative Deep Learning for Recommender Systems (2014, neutral): “uct descriptions for recommendation. CF-based methods [19, 23] use the past activities or preferences, such as user ratings on items, without using user or product content information. Hybrid methods [1, 20, 15] seek to get the best of both worlds by combining content-based and CF-based methods. Due”
• Relational Collaborative Topic Regression for Recommender Systems (2015, methodology): “Hybrid methods [2], [3], [6], [12], [15], [16], [17], [20], [32], [34], [40], [43], [47], [48] combine both content-based methods and CF based methods by ensemble techniques.”