Machine Learning Approach to Detect Online Shopping Addiction-Reference-Cited by-同舟云学术

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Machine Learning Approach to Detect Online Shopping Addiction

Published:2022-02-23 Issue: Volume: Page:
ISSN:
Container-title:2022 2nd International Conference on Advanced Research in Computing (ICARC)
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Author:

A. G. S Nawodya¹,Kumara B. T. G. S.¹

Affiliation:

1. Sabaragamuwa University of Sri Lanka,Department of Computing & Information Systems,Belihuloya,Sri Lanka

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9752770/9753716/09754020.pdf?arnumber=9754020

Reference23 articles.

1. Towards an understanding of Internet-based problem shopping behaviour: The concept of online shopping addiction and its proposed predictors

2. Characteristics of online compulsive buying in Parisian students

3. Shopping addiction and emotion based decision-making in consumers. A data mining approach;halkiopoulos;International Journal of Recent Scientific Research,2020

4. Motivation for online impulse buying: A two-factor theory perspective

5. Phases of Shopping Addiction Evidenced by Experiences of Compulsive Buyers

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Comparative Analysis of Data Mining Classification Techniques for Prediction of Problematic Internet Shopping;International Journal of Applied Sciences & Development;2024-06-14

2. Review of Persuasive User Interface as Strategy for Technology Addiction in Virtual Environments;2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct);2022-10

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