Content-Based News Recommendation

By Michal Kompan, Maria Bielikova. 2010

128 citations recorded by the source corpus.

Subfields: 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 Computer Vision and Pattern Recognition

1. Qiang Yang
2. Xing Xie
3. Zhongqi Lu
4. Zhicheng Dou
5. Xiting Wang
6. Zhenhui Jessie Li
7. Nicholas Jing Yuan
8. Yasha Wang

In Information Systems

1. Xing Xie
2. Fuzheng Zhang
3. Qiang Yang
4. Xiting Wang
5. Jianxun Lian
6. Zhongqi Lu
7. Zhicheng Dou
8. Zhenhui Jessie Li

Citations in the corpus

• DRN: A Deep Reinforcement Learning Framework for News Recommendation (2018, methodology): “The current methods can be generally categorized as content based methods [19, 22, 33], collaborative filtering based methods [11, 28, 34], and hybrid methods [12, 24, 25].”
• DKN: Deep Knowledge-Aware Network for News Recommendation (2018, neutral): “Therefore, a large amount of content-based or hybrid methods have been proposed [2, 22, 27, 34, 39].”
• News recommender systems - Survey and roads ahead (2018, unknown): “Kompan and Bieliková [98] 2010 CB – SME.”
• Explainable Recommendation through Attentive Multi-View Learning (2019, methodology): “Many methods have been proposed to improve recommendation accuracy, including content-based (Kompan and Bieliková 2010), collaborative filtering-based (Das et al.”
• Content-Based Collaborative Filtering for News Topic Recommendation (2015, background): “Some works (Kompan and Bieliková 2010) adopt the content-based approach.”