[1]胡磊,蔡红霞,俞涛. 双重聚类的协同过滤算法在智能家居中的应用[J].计算机技术与发展,2017,27(02):100-105.
　HU Lei,CAI Hong-xia,YU Tao. Application of Collaborative Filtering Recommendation Based on Double Clustering in Smart Home System[J].,2017,27(02):100-105.
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 双重聚类的协同过滤算法在智能家居中的应用()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
27
期数:
2017年02期
页码:
100-105
栏目:
应用开发研究
出版日期:
2017-02-10

文章信息/Info

Title:
 Application of Collaborative Filtering Recommendation Based on Double Clustering in Smart Home System
文章编号:
1673-629X（2017)02-0100-06
作者:
 胡磊; 蔡红霞; 俞涛
 上海大学机电工程与自动化学院
Author(s):
 HU Lei; CAI Hong-xia; YU Tao
关键词:
 ; 智能家居; K-means; 聚类; 最近邻居; 协同过滤
Keywords:
 ; smart home; K-means; clustering; the nearest neighbors; collaborative filtering
分类号:
TP301.6
文献标志码:
A
摘要:
 针对智能家居系统中用户获取有效信息困难的问题,提出基于用户和环境双重聚类的协同过滤推荐算法.利用K-means算法分别对智能家居系统中的用户和环境进行聚类,找出目标用户和所处家居环境的最近邻居.使用欧氏距离为度量计算目标用户和系统其他用户之间、目标用户所处家居环境和系统其他家居环境之间的综合相似度.从最近邻居之间选出与目标用户最相似的前K个推荐给目标用户,实现对推荐算法的优化.实验结果表明,与传统的协同过滤算法,以及基于用户或环境单一变量的协同过滤算法相比,文中采用的算法推荐精度更高,实时性和可扩展性更好.
Abstract:
 To deal with the difficulty of acquiring effective information in smart home system for users,a collaborative filtering recommendation based on users and environment double clustering is proposed.It applies K-means method to cluster the users and environment and find out the nearest neighbors of target user and home environment.Then computes the comprehensive similarity between target user and other users,home environment of target user and other home enviroment in system.Chooses the first K recommendation in the nearest neighbors to target users,realizing the optirization of recommendation.Experimental results demonstrate that the algorithm can improve the accuracy of recommendation compared with the traditional one and the one based on user or environment,with better real-time and sealability.

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更新日期/Last Update: 2017-05-11