Design and Application of Personalized Recommendation Algorithm Model Based on E-Commerce Platform Data

Qi Ding, Zhigang Zhu

2022

Abstract

The algorithm models of K-means, Item-CF and User-CF based on Python environment can well realize various functions of personalized recommendation service system of e-commerce platform, and can formulate different recommendation service strategies for different user groups, which can effectively solve the problem of adaptation between e-commerce platform and users' needs and improve users' purchase efficiency and experience. Therefore, this paper takes the running data of e-commerce platform as the research object, relies on data processing class libraries such as Numpy and Pandas in Python environment, builds a personalized recommendation engine, and forms a personalized recommendation service system adapted to the call of Web Server through systematic encapsulation. Personalized recommendation service system will be between user I/O interface and e-commerce platform, and adopt MVC technology framework as the core design, and design API interfaces that can be called according to different application scenarios, so as to achieve a high degree of integration between recommendation system and e-commerce platform, meet the recommendation service strategy formulation requirements of e-commerce platform, and at the same time, it has good technical expansion performance in improving personalized recommendation.

Paper Citation

in Harvard Style

Ding Q. and Zhu Z. (2022). Design and Application of Personalized Recommendation Algorithm Model Based on E-Commerce Platform Data. In Proceedings of the 4th International Conference on Economic Management and Model Engineering - Volume 1: ICEMME; ISBN 978-989-758-636-1, SciTePress, pages 310-315. DOI: 10.5220/0012030000003620

in Bibtex Style

@conference{icemme22,
author={Qi Ding and Zhigang Zhu},
title={Design and Application of Personalized Recommendation Algorithm Model Based on E-Commerce Platform Data},
booktitle={Proceedings of the 4th International Conference on Economic Management and Model Engineering - Volume 1: ICEMME},
year={2022},
pages={310-315},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012030000003620},
isbn={978-989-758-636-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 4th International Conference on Economic Management and Model Engineering - Volume 1: ICEMME
TI - Design and Application of Personalized Recommendation Algorithm Model Based on E-Commerce Platform Data
SN - 978-989-758-636-1
AU - Ding Q.
AU - Zhu Z.
PY - 2022
SP - 310
EP - 315
DO - 10.5220/0012030000003620
PB - SciTePress