Consumer Behavior Prediction Based on Machine Learning Scenarios

DOI

10.2991/978-94-6463-030-5_43How to use a DOI?

Keywords

Consumer Behavior Prediction; Machine Learning; Decision Tree Algorithm; Recurrent Neural Networks; FMRI

Abstract

Consumer behavior prediction is an important part of the business analysis and strategy development process. With the development of AI technology, machine learning has been also applied to consumer behavior prediction. This paper introduces some common and novel consumer behavior prediction methods, including decision tree algorithm, recurrent neural networks (RNNs) algorithm, and the application of fMRI in machine learning. The advantages and limitations of these methods are clarified by analyzing the practical cases based on these methods. This paper first introduces the background of consumer behavior prediction and review some existing prediction methods. Subsequently an introduction and review of the three selected prediction methods and the cases they participated in are demonstrated accordingly. Afterwards, the advantages of the three methods and the drawbacks of them are evaluated by analyzing the three cases. Then, some measures are proposed to improve the performance of the models to pave the path for future development of consumer behavior prediction in terms of machine learning supports. These analytical results offer guideline for the future development of consumer behavior prediction.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Zhengyi Hu
PY  - 2022
DA  - 2022/12/20
TI  - Consumer Behavior Prediction Based on Machine Learning Scenarios
BT  - Proceedings of the 2022 International Conference on Bigdata Blockchain and Economy Management (ICBBEM 2022)
PB  - Atlantis Press
SP  - 410
EP  - 419
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-030-5_43
DO  - 10.2991/978-94-6463-030-5_43
ID  - Hu2022
ER  -