Website Intelligent Recommendation Based on K-means and Apriori Algorithms
Shaohua Zhang, Changhua Liu, Qiaodan Li
Available Online March 2018.
- 10.2991/acaai-18.2018.44How to use a DOI?
- Recommendation; Association rules; Apriori; K-means
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.
- © 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/).
Cite this article
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 -