Big Data Analysis of Personalized Recommendation in E-Commerce
Authors
Xijun Linxijun.lin@ucdconnect.ie
University College Dublin, Quinn Business School, Dublin 4, Dublin, Ireland
Corresponding Author
Xijun Linxijun.lin@ucdconnect.ie
Available Online 8 April 2022.
- DOI
- 10.2991/assehr.k.220401.147How to use a DOI?
- Keywords
- Principal Component Analysis; Association Analysis; Super Vector Machine; E-commence; Users’ Behavior
- Abstract
The personalized recommendation analysis for users’ behaviors in e-commerce platform by big data analysis. Study on what kind of factors will affect on personal recommendations for goods on Amazon more effective by using Principal Component Analysis (PCA), Association Analysis and SVM (Super Vector Machine) Model. Using RFM Model to increase platform sales by analysis those data. This model aims to improve the accuracy and effectiveness of personalized recommendation, therefore improving the sales of goods on platform and the satisfaction of users.
- Copyright
- © 2022 The Authors. Published by Atlantis Press SARL.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license.
Cite this article
TY - CONF AU - Xijun Lin PY - 2022 DA - 2022/04/08 TI - Big Data Analysis of Personalized Recommendation in E-Commerce BT - Proceedings of the 2022 International Conference on Social Sciences and Humanities and Arts (SSHA 2022) PB - Atlantis Press SP - 768 EP - 771 SN - 2352-5398 UR - https://doi.org/10.2991/assehr.k.220401.147 DO - 10.2991/assehr.k.220401.147 ID - Lin2022 ER -