Ensemble learning methods for pay-per-click campaign management

作者：

Highlights：

• We propose using ensemble techniques to improve pay-per-click campaign management.

• Actual data containing pay-per-click campaign results is used for our analysis.

• Four base classifiers are analyzed as inputs to four ensemble modeling techniques.

• A MetaCost ensemble predicted the highest campaign portfolio profit.

摘要

•We propose using ensemble techniques to improve pay-per-click campaign management.•Actual data containing pay-per-click campaign results is used for our analysis.•Four base classifiers are analyzed as inputs to four ensemble modeling techniques.•A MetaCost ensemble predicted the highest campaign portfolio profit.

论文关键词：Sponsored search,Pay-per-click advertising,Classification,Ensemble modeling

论文评审过程：Available online 4 February 2015.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.01.047