Real-time Periodic Advertisement Recommendation Optimization under Delivery Constraint using Quantum-inspired Computer

Fan Mo, Huida Jiao, Shun Morisawa, Makoto Nakamura, Koichi Kimura, Hisanori Fujisawa, Masafumi Ohtsuka, Hayato Yamana

Abstract

For commercial companies, tuning advertisement delivery to achieve a high conversion rate (CVR) is crucial for improving advertising effectiveness. Because advertisers use demand-side platforms (DSP) to deliver a certain number of ads within a fixed period, it is challenging for DSP to maximize CVR while satisfying delivery constraints such as the number of delivered ads in each category. Although previous research aimed to optimize the combinational problem under various constraints, its periodic updates remained an open question because of its time complexity. Our work is the first attempt to adopt digital annealers (DAs), which are quantum-inspired computers manufactured by Fujitsu Ltd., to achieve real-time periodic ad optimization. With periodic optimization in a short time, we have much chance to increase ad recommendation precision. First, we exploit each user’s behavior according to his visited web pages and then predict his CVR for each ad category. Second, we transform the optimization problem into a quadratic unconstrained binary optimization model applying to the DA. The experimental evaluations on real log data show that our proposed method improves accuracy score from 0.237 to 0.322 while shortening the periodic advertisement recommendation from 526s to 108s (4.9 times speed-up) in comparison with traditional algorithms.

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Paper Citation


in Harvard Style

Mo F., Jiao H., Morisawa S., Nakamura M., Kimura K., Fujisawa H., Ohtsuka M. and Yamana H. (2021). Real-time Periodic Advertisement Recommendation Optimization under Delivery Constraint using Quantum-inspired Computer. In Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-509-8, pages 431-441. DOI: 10.5220/0010414704310441


in Bibtex Style

@conference{iceis21,
author={Fan Mo and Huida Jiao and Shun Morisawa and Makoto Nakamura and Koichi Kimura and Hisanori Fujisawa and Masafumi Ohtsuka and Hayato Yamana},
title={Real-time Periodic Advertisement Recommendation Optimization under Delivery Constraint using Quantum-inspired Computer},
booktitle={Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2021},
pages={431-441},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010414704310441},
isbn={978-989-758-509-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Real-time Periodic Advertisement Recommendation Optimization under Delivery Constraint using Quantum-inspired Computer
SN - 978-989-758-509-8
AU - Mo F.
AU - Jiao H.
AU - Morisawa S.
AU - Nakamura M.
AU - Kimura K.
AU - Fujisawa H.
AU - Ohtsuka M.
AU - Yamana H.
PY - 2021
SP - 431
EP - 441
DO - 10.5220/0010414704310441