Design and implementation of an intelligent recommendation system for product information on an e-commerce platform based on machine learning

Peng, Nianjiao; Xiao, Xunyong; Wu, Di; Li, Ang; Wen, Manhong

doi:10.1117/12.3013353

International Conference on Internet of Things and Machine Learning (IoTML 2023) 2023

DOI: 10.1117/12.3013353

|View full text |Cite

Design and implementation of an intelligent recommendation system for product information on an e-commerce platform based on machine learning

Nianjiao Peng,

Xunyong Xiao,

Di Wu

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 5 publications

(4 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

Personalized Recommendation Research Based on Logistic Regression Algorithm for Amazon Product Reviews

Wang,

2024

JIEM

View full text Add to dashboard Cite

<p class="MsoNormal" align="justify"><span style="font-family: Times New Roman;">This study explores personalized recommendation strategies within Amazon's product review system using the Logistic Regression algorithm. By analyzing user behavior and review data, a predictive model was developed to forecast user preferences for specific products. The research employed extensive real-world data and validated the model's effectiveness and accuracy through empirical analysis. Findings indicate that the proposed personalized recommendation system significantly enhances user experience and increases product sales. The study contributes an effective recommendation algorithm for e-commerce platforms, offering practical implications for enhancing user engagement and optimizing marketing strategies in competitive markets.</span></p>

show abstract

Personalized Recommendation Research Based on Logistic Regression Algorithm for Amazon Product Reviews

Wang,

2024

JIEM

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

hi@scite.ai

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Design and implementation of an intelligent recommendation system for product information on an e-commerce platform based on machine learning

Cited by 1 publication

References 5 publications

Personalized Recommendation Research Based on Logistic Regression Algorithm for Amazon Product Reviews

Personalized Recommendation Research Based on Logistic Regression Algorithm for Amazon Product Reviews

Contact Info

Product

Resources

About