Making Large Language Models Better Knowledge Miners for Online Marketing with Progressive Prompting Augmentation

C Gan, D Yang, B Hu, Z Liu, Y Shen, Z Zhang… - arXiv preprint arXiv …, 2023 - arxiv.org
Nowadays, the rapid development of mobile economy has promoted the flourishing of online
marketing campaigns, whose success greatly hinges on the efficient matching between user …

Marketing budget allocation with offline constrained deep reinforcement learning

T Cai, J Jiang, W Zhang, S Zhou, X Song, L Yu… - Proceedings of the …, 2023 - dl.acm.org
We study the budget allocation problem in online marketing campaigns that utilize
previously collected offline data. We first discuss the long-term effect of optimizing marketing …

A survey of deep causal models and their industrial applications

Z Li, Z Zhu, S Zheng, Z Guo, S Qiang, Y Zhao - arXiv preprint arXiv …, 2022 - arxiv.org
The concept of causality plays a significant role in human cognition. In the past few decades,
causal effect estimation has been well developed in many fields, such as computer science …

Imbalance-aware uplift modeling for observational data

X Chen, Z Liu, L Yu, L Yao, W Zhang, Y Dong… - Proceedings of the …, 2022 - ojs.aaai.org
Uplift modeling aims to model the incremental impact of a treatment on an individual
outcome, which has attracted great interests of researchers and practitioners from different …

[HTML][HTML] A new method for solving the mobile payment scheduling problem using harris hawks optimization algorithm during the COVID-19 pandemic

W Sun, C She, M Khalilzadeh, HZ Mao… - Information Systems and e …, 2023 - Springer
Abstract The Coronavirus Disease 2019 (COVID-19) epidemic is causing once-in-a-century
upheavals in global civilization. Payment systems have advanced lately, from simple cash or …