Website Intelligent Recommendation Based on K-means and Apriori Algorithms

DOI

10.2991/acaai-18.2018.44How to use a DOI?

Keywords

Recommendation; Association rules; Apriori; K-means

Abstract

The recommended algorithm is one of the most popular applications of today. Firstly, the original data is cleaned and processed, and then the association rules model and user value analysis model are established in this paper. Secondly, a Apriori algorithm is used to analyze the relationship between user history access records and the user group of K-means algorithm is used to divide value. Finally, the experimental results show that the results of the output of the association rules and the clustering analysis of the user value have some reference significance.

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/).

Download article (PDF)

TY  - CONF
AU  - Shaohua Zhang
AU  - Changhua Liu
AU  - Qiaodan Li
PY  - 2018/03
DA  - 2018/03
TI  - Website Intelligent Recommendation Based on K-means and Apriori Algorithms
BT  - Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018)
PB  - Atlantis Press
SP  - 188
EP  - 190
SN  - 1951-6851
UR  - https://doi.org/10.2991/acaai-18.2018.44
DO  - 10.2991/acaai-18.2018.44
ID  - Zhang2018/03
ER  -