Research on Personalized E-Commerce Recommendation Platform

DOI

10.2991/icsser-18.2018.59How to use a DOI?

Keywords

Internet; E-Commerce; Personalized recommendation; Deep learning

Abstract

With the deep integration of Internet and E-Commerce, using network technology to analyze and explore users' interest, and providing personalized services for them are becoming a popular application of online transactions. In order to solve the problems of low recommendation quality and poor real-time performance existing in personalized E-Commerce recommendation platform, this paper tries to establish a multi-hidden layer artificial neural network learning model to deeply explore the potential interest of users, so as to improve the recommendation quality. Meanwhile, this paper adopts the cloud computing technology to parallelize CPU clusters for improving recognition speed and realizing real-time demand.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Qiong Li
AU  - Fang Chai
AU  - Li Chen
PY  - 2018/10
DA  - 2018/10
TI  - Research on Personalized E-Commerce Recommendation Platform
BT  - Proceedings of the 2018 International Conference on Social Science and Education Reform (ICSSER 2018)
PB  - Atlantis Press
SP  - 248
EP  - 251
SN  - 2352-5398
UR  - https://doi.org/10.2991/icsser-18.2018.59
DO  - 10.2991/icsser-18.2018.59
ID  - Li2018/10
ER  -