Ant Colony Clustering Algorithm for Personalized Recommendation of E-Commerce

被引：1
|
作者：
Li, Bin [1 ,2 ,3 ]
机构：
[1] Nanchang Vocat Univ, Nanchang 330500, Jiangxi, Peoples R China
[2] Nanchang Vocat Coll, Informat Technol Dept, Gen Party Branch, Nanchang, Jiangxi, Peoples R China
[3] Jiangxi Prov Intermediate Double Qualificat Teach, Nanchang, Jiangxi, Peoples R China
来源：
2020 5TH INTERNATIONAL CONFERENCE ON MECHANICAL, CONTROL AND COMPUTER ENGINEERING (ICMCCE 2020) | 2020年
关键词：
data mining; e-commerce; ant colony; clustering; algorithm; ELECTRONIC COMMERCE; ADOPTION;
D O I：
10.1109/ICMCCE51767.2020.00407
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
How to use the data mining and analysis algorithm to carry out e-commerce recommendation has become one of the important contents of the current information technology development. Therefore, in this paper, research on ant colony clustering algorithm for personalized recommendation of e-commerce was proposed. The domestic and foreign research on e-commerce recommendation was simply summarized. Through the classical clustering algorithm in ant colony algorithm, an e-commerce recommendation algorithm was designed. Then the experimental results of the proposed algorithm prove that the algorithm is a very effective e-commerce recommendation algorithm, but also better than other e-commerce recommendation algorithms.
引用
收藏
页码：1855 / 1860
页数：6
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