Evaluating and Optimizing Online Advertising: Forget the Click, but There Are Good Proxies
By Brian M. D’Alessandro, Rod Hook, Claudia Perlich, Foster J. Provost. 2015
49 citations recorded by the source corpus.
Subfields: Management Science and Operations Research, Marketing, Sociology and Political Science
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Management Science and Operations Research
- Weinan Zhang
- Jun Wang
- Brian M. D’Alessandro
- Shuai Yuan
- Foster J. Provost
- Claudia Perlich
- Ori Stitelman
- Troy Raeder
In Marketing
- Weinan Zhang
- Anja Lambrecht
- Jun Wang
- Brian M. D’Alessandro
- Catherine E. Tucker
- Shuai Yuan
- Foster J. Provost
- P. K. Kannan
In Sociology and Political Science
- Anja Lambrecht
- Foster J. Provost
- Catherine E. Tucker
- Claudia Perlich
- Weinan Zhang
- Brian M. D’Alessandro
- Jun Wang
- Benedict G. C. Dellaert
Citations in the corpus
- Conscientious Classification: A Data Scientist's Guide to Discrimination-Aware Classification (2017, neutral): “Another, called proxy learning , 21 uses an alternative proxy label that is correlated with the main label of interest, but is much more abundant in the data.”
- Optimal real-time bidding for display advertising (2014, background): “In [13] the authors study the evaluation measures of the display advertising performance and they find the site visit turns to be a better proxy than the user click.”
- When Does Retargeting Work? Information Specificity in Online Advertising (2013, background): “However, as discussed by Dalessandro et al. (2012), clicks are not very relevant for understanding the effectiveness of the type of display advertising we study.”
- Machine learning for targeted display advertising: transfer learning in action (2013, methodology): “in depth to convince ourselves that it indeed is appropriate (Dalessandro et al. 2012)).”