Computational advertising and recommender systems

By Andrei Z. Broder. 2008

68 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Marketing

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. Qiang Yang
2. Wei-Wei Tu
3. Yang Yu
4. Yuqiang Chen
5. Jing Jiang
6. Yi-Qi Hu
7. Bernhard Schölkopf
8. Wenyuan Dai

In Information Systems

1. Qiang Yang
2. Yang Yu
3. Jing Jiang
4. Qiming Diao
5. Chong Wang
6. Minghui Qiu
7. Chao-Yuan Wu
8. Alex Smola

In Marketing

1. Jing Jiang
2. Qiang Yang
3. Qiming Diao
4. Chong Wang
5. Minghui Qiu
6. Chao-Yuan Wu
7. Alex Smola

Citations in the corpus

• Multi-Fidelity Automatic Hyper-Parameter Tuning via Transfer Series Expansion (2019, background): “During the past decades, machine learning has achieved great successes in many applications, e.g., computer vision (Bradski 1998), recommender system (Broder 2008), financial market analysis (Ball 2013), and so on.”
• Recommender Systems (2016, unknown): “More recent discussions of such systems may be found in [106, 107].”
• Jointly modeling aspects, ratings and sentiments for movie recommendation (JMARS) (2014, background): “This is the key source of information in search, ranking and advertising systems [4].”