[1]王晨阳,刘垣,郭李华,等.融合位置相似性度量的快消品电商网站推荐算法[J].福建工程学院学报,2017,15(06):586-590.[doi:10.3969/j.issn.1672-4348.2017.06.016]
 Wang Chenyang,Liu Yuan,Guo Lihua,et al.An FMCG e-commerce website recommendation algorithm with the fusion of location similarity measurement[J].Journal of FuJian University of Technology,2017,15(06):586-590.[doi:10.3969/j.issn.1672-4348.2017.06.016]
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融合位置相似性度量的快消品电商网站推荐算法()
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《福建工程学院学报》[ISSN:2097-3853/CN:35-1351/Z]

卷:
第15卷
期数:
2017年06期
页码:
586-590
栏目:
出版日期:
2017-12-25

文章信息/Info

Title:
An FMCG e-commerce website recommendation algorithm with the fusion of location similarity measurement
作者:
王晨阳刘垣郭李华肖琳
福建工程学院信息科学与工程学院
Author(s):
Wang Chenyang Liu Yuan Guo Lihua Xiao Lin
School of Information Science and Engineering, Fujian University of Technology
关键词:
推荐系统 协同过滤 位置服务 电子商务 快消品
Keywords:
recommendation system collaborative filtering location-based service e-commerce fast moving consumer goods(FMCG)
分类号:
TP391
DOI:
10.3969/j.issn.1672-4348.2017.06.016
文献标志码:
A
摘要:
提出一种融合位置相似性度量的协同过滤推荐算法(CF-FLSM)。算法融合位置相似性度量进行加权计算用户间的兴趣相似度,从而为目标用户产生推荐结果。将CF-FLSM应用于一个具体的快消品电商网站,得出的推荐结果与传统使用余弦相似性的协同过滤推荐算法(CF)相比,精确率和召回率分别提高了3.74%和3.91%。
Abstract:
A collaborative filtering recommendation algorithm with the fusion of location similarity measurement (CG-FLSM) was proposed. This algorithm integrated location similarity measurement to compute preference similarity between users, thus generating recommendation results for the target user. Finally the CF-FLSM was applied to a specific FMCG e-commerce website, and experimental results showed that, compared with the traditional collaborative filtering recommendation algorithm (CF) using cosine similarity, its precision rate and recall rate were increased by 3.74% and 3.91% respectively.

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更新日期/Last Update: 2017-12-25