Proceedings of the 2018 International Conference on Social Science and Education Reform (ICSSER 2018)

Research on Personalized E-Commerce Recommendation Platform

Authors
Qiong Li, Fang Chai, Li Chen
Corresponding Author
Qiong Li
Available Online October 2018.
DOI
https://doi.org/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.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
2018 International Conference on Social Science and Education Reform (ICSSER 2018)
Part of series
Advances in Social Science, Education and Humanities Research
Publication Date
October 2018
ISBN
978-94-6252-600-6
ISSN
2352-5398
DOI
https://doi.org/10.2991/icsser-18.2018.59How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

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  - 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  - https://doi.org/10.2991/icsser-18.2018.59
ID  - Li2018/10
ER  -