Research on Personalized E-Commerce Recommendation Platform
Qiong Li, Fang Chai, Li Chen
Available Online October 2018.
- https://doi.org/10.2991/icsser-18.2018.59How to use a DOI?
- Internet; E-Commerce; Personalized recommendation; Deep learning
- 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.
- 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 -