An Intelligent and Personalized Tobacco Brand Recommendation Method

被引:0
|
作者
Song Nan [1 ]
Hou Jidong [2 ]
Liu Peijiang [1 ]
Han Huijian [3 ]
Liu Zheng [3 ]
Zhang Rui [3 ]
机构
[1] Shandong Tobacco Res Inst, Jinan 250014, Shandong, Peoples R China
[2] Jinan Shandong Tobacco Co Ltd, Jinan 250014, Shandong, Peoples R China
[3] Shandong Univ Finance & Econ, Jinan 250014, Shandong, Peoples R China
关键词
Tobacco brand; Personalized recommendation; User similarity; Cosine distance;
D O I
10.1109/ICITBS.2015.30
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper aims to solve the intelligent and personalized tobacco brand recommendation problem, which greatly affects the sales performance of tobacco enterprises. Firstly, we discuss how to mine the internal correlations between different users to compute user similarity. Particularly, we estimate user similarity by constructing user feature vectors using Cosine distance. Secondly, a novel intelligent and personalized tobacco brand recommendation algorithm is given, and the top ranked tobacco brands are output as the tobacco brand recommendation results. Finally, experiments test the effectiveness of the proposed algorithm by two main aspects, and positive results are achieved.
引用
收藏
页码:98 / 101
页数:4
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