Paper
11 October 2023 Prediction and analysis of in-vehicle coupon acceptance behavior
Yurou He, Yunpeng Chen
Author Affiliations +
Proceedings Volume 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023); 1280002 (2023) https://doi.org/10.1117/12.3003856
Event: 6th International Conference on Computer Information Science and Application Technology (CISAT 2023), 2023, Hangzhou, China
Abstract
In order to promote the coupon distribution in the Web 3.0 scenario and explore new areas of marketing strategy, this research focuses on the user-delivery mechanism of coupons in different driving mobile scenes, introduces the data mining method, and proposes the fusion algorithm integrating Logistic Regression, SVM, Random Forest and Adaboost based on stacking model to build the prediction model of in-vehicle coupon acceptance behavior. By comparing the performance of the fusion model with four single models, the results show that the fusion framework can effectively improve the model training effect. In addition, this paper uses the statistical grouping method to analyze the driving distance and the types of coupons and puts forward the strategy of coupon delivery: coupons are issued to users within 15 minutes' drive of the shop, and users with a drive above 25 minutes will issue takeaway coupons instead.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Yurou He and Yunpeng Chen "Prediction and analysis of in-vehicle coupon acceptance behavior", Proc. SPIE 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023), 1280002 (11 October 2023); https://doi.org/10.1117/12.3003856
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KEYWORDS
Data modeling

Education and training

Machine learning

Performance modeling

Random forests

Decision trees

Statistical modeling

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