SEM: A Softmax-based Ensemble Model for CTR estimation in Real-Time Bidding advertising

Wen Yuan Zhu, Chun Hao Wang, Wen Yueh Shih, Wen-Chih Peng, Jiun-Long Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

In Real-Time Bidding (RTB) advertising, evaluating the Click-Through Rate (CTR) of a bid request and an ad is important for bidding strategy optimization on Demand-Side Platforms (DSPs). The regression-based approaches are popular for CTR estimation in RTB since this kind of approach is highly efficient and scalable. The information of the bid request and the ad contains categorical attributes (such URL) and numerical attributes (such ad size). To vectorize the information for the input of regression-based approaches, the categorical attributes will be expanded to several binary features in general. However, some categorical attributes have infinite possible values (such as URL). Thus, for these attributes, only observed values in training will be transformed into binary features. If there is a new attribute or value in online environment, this information will be lost after vectorization. In this paper, we first exploit the feature hashing trick to transform the categorical and numerical attributes into the large fixed size vector. Since the vector is large and sparse, we propose a Softmax-based Ensemble Model, SEM, which adopts only a few key features after feature hashing for CTR estimation. The experimental results demonstrate that our proposed approach is able to adapt to the harsh environments in RTB, and outperforms the state-of-the-art approaches effectively when only less than 50 features are adopted in two real datasets.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5-12
Number of pages8
ISBN (Electronic)9781509030156
DOIs
StatePublished - 17 Mar 2017
Event2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017 - Jeju Island, Korea, Republic of
Duration: 13 Feb 201716 Feb 2017

Publication series

Name2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017

Conference

Conference2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017
CountryKorea, Republic of
CityJeju Island
Period13/02/1716/02/17

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    Zhu, W. Y., Wang, C. H., Shih, W. Y., Peng, W-C., & Huang, J-L. (2017). SEM: A Softmax-based Ensemble Model for CTR estimation in Real-Time Bidding advertising. In 2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017 (pp. 5-12). [7881698] (2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIGCOMP.2017.7881698