Practical Lessons from Predicting New User Demographics for Ad Targeting

Musen Wen, Zhen Xia, Deepak Kumar Vasthimal
Proceedings of the 2nd Workshop on Online Recommder Systems and User Modeling, PMLR 109:59-67, 2019.

Abstract

Programmatic ad buying, the use of technology to automate and optimize the ad buying process in real-time, has been emerging to be the major form of online advertising. For each online campaign, advertisers generally want to specify a certain group of audience that they want to target at. Among these, demographics (user age and gender) is the fundamental and most common targeting option. On the other side, due to the huge volume of bid-requests flowing into the exchange, majority of those users (i.e. cookies) are either completely new to the ad platform or has too little historical behavior information to determine their demographics. In this paper, we present and discuss the methods, system and practical lessons in tackling this problem at massive scale.

Cite this Paper

BibTeX
@InProceedings{pmlr-v109-wen19a, title = {Practical Lessons from Predicting New User Demographics for Ad Targeting}, author = {Wen, Musen and Xia, Zhen and Vasthimal, Deepak Kumar}, booktitle = {Proceedings of the 2nd Workshop on Online Recommder Systems and User Modeling}, pages = {59--67}, year = {2019}, editor = {Vinagre, João and Jorge, Alípio Mário and Bifet, Albert and Al-Ghossein, Marie}, volume = {109}, series = {Proceedings of Machine Learning Research}, month = {19 Sep}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v109/wen19a/wen19a.pdf}, url = {https://proceedings.mlr.press/v109/wen19a.html}, abstract = {Programmatic ad buying, the use of technology to automate and optimize the ad buying process in real-time, has been emerging to be the major form of online advertising. For each online campaign, advertisers generally want to specify a certain group of audience that they want to target at. Among these, demographics (user age and gender) is the fundamental and most common targeting option. On the other side, due to the huge volume of bid-requests flowing into the exchange, majority of those users (i.e. cookies) are either completely new to the ad platform or has too little historical behavior information to determine their demographics. In this paper, we present and discuss the methods, system and practical lessons in tackling this problem at massive scale.} }
Endnote
%0 Conference Paper %T Practical Lessons from Predicting New User Demographics for Ad Targeting %A Musen Wen %A Zhen Xia %A Deepak Kumar Vasthimal %B Proceedings of the 2nd Workshop on Online Recommder Systems and User Modeling %C Proceedings of Machine Learning Research %D 2019 %E João Vinagre %E Alípio Mário Jorge %E Albert Bifet %E Marie Al-Ghossein %F pmlr-v109-wen19a %I PMLR %P 59--67 %U https://proceedings.mlr.press/v109/wen19a.html %V 109 %X Programmatic ad buying, the use of technology to automate and optimize the ad buying process in real-time, has been emerging to be the major form of online advertising. For each online campaign, advertisers generally want to specify a certain group of audience that they want to target at. Among these, demographics (user age and gender) is the fundamental and most common targeting option. On the other side, due to the huge volume of bid-requests flowing into the exchange, majority of those users (i.e. cookies) are either completely new to the ad platform or has too little historical behavior information to determine their demographics. In this paper, we present and discuss the methods, system and practical lessons in tackling this problem at massive scale.
APA
Wen, M., Xia, Z. & Vasthimal, D.K.. (2019). Practical Lessons from Predicting New User Demographics for Ad Targeting. Proceedings of the 2nd Workshop on Online Recommder Systems and User Modeling, in Proceedings of Machine Learning Research 109:59-67 Available from https://proceedings.mlr.press/v109/wen19a.html.

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