TY - GEN
T1 - An Alternative Auction System to Generalized Second-Price for Real-Time Bidding Optimized Using Genetic Algorithms
AU - Miralles-Pechuán, Luis
AU - Jiménez, Fernando
AU - García, Josá Manuel
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2022
Y1 - 2022
N2 - Real-Time Bidding is a new Internet advertising system that has become very popular in recent years. This system works like a global auction where advertisers bid to display their impressions in the publishers’ ad slots. The most popular system to select which advertiser wins each auction is the Generalized second-price auction, in which the advertiser that offers the most, wins the bet and is charged with the price of the second largest bet. In this paper, we propose an alternative betting system with a new approach that not only considers the economic aspect, but also other relevant factors for the functioning of the advertising system. The factors that we consider are, among others, the benefit that can be given to each advertiser, the probability of conversion from the advertisement, the probability that the visit is fraudulent, how balanced are the networks participating in RTB and if the advertisers are not paying over the market price. In addition, we propose a methodology based on genetic algorithms to optimize the selection of each advertiser. We also conducted some experiments to compare the performance of the proposed model with the famous Generalized Second-Price method. We think that this new approach, which considers more relevant aspects besides the price, offers greater benefits for RTB networks in the medium and long-term.
AB - Real-Time Bidding is a new Internet advertising system that has become very popular in recent years. This system works like a global auction where advertisers bid to display their impressions in the publishers’ ad slots. The most popular system to select which advertiser wins each auction is the Generalized second-price auction, in which the advertiser that offers the most, wins the bet and is charged with the price of the second largest bet. In this paper, we propose an alternative betting system with a new approach that not only considers the economic aspect, but also other relevant factors for the functioning of the advertising system. The factors that we consider are, among others, the benefit that can be given to each advertiser, the probability of conversion from the advertisement, the probability that the visit is fraudulent, how balanced are the networks participating in RTB and if the advertisers are not paying over the market price. In addition, we propose a methodology based on genetic algorithms to optimize the selection of each advertiser. We also conducted some experiments to compare the performance of the proposed model with the famous Generalized Second-Price method. We think that this new approach, which considers more relevant aspects besides the price, offers greater benefits for RTB networks in the medium and long-term.
KW - Advertising exchange system
KW - Advertising revenue system calculation
KW - Generalized second-price
KW - Genetic algorithms
KW - Online advertising networks
KW - Real-time bidding
UR - http://www.scopus.com/inward/record.url?scp=85116022888&partnerID=8YFLogxK
U2 - 10.1007/978-981-16-2380-6_8
DO - 10.1007/978-981-16-2380-6_8
M3 - Conference contribution
AN - SCOPUS:85116022888
SN - 9789811623790
T3 - Lecture Notes in Networks and Systems
SP - 83
EP - 107
BT - Proceedings of 6th International Congress on Information and Communication Technology, ICICT 2021
A2 - Yang, Xin-She
A2 - Sherratt, Simon
A2 - Dey, Nilanjan
A2 - Joshi, Amit
PB - Springer Science and Business Media Deutschland GmbH
T2 - 6th International Congress on Information and Communication Technology, ICICT 2021
Y2 - 25 February 2021 through 26 February 2021
ER -