[1]张龙昌,张洪锐. 数字资源云服务推荐系统设计[J].计算机技术与发展,2017,27(08):139-144.
　ZHANG Long-chang,ZHANG Hong-rui. Design of Recommender System with Cloud Services of Digital Resource[J].,2017,27(08):139-144.
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 数字资源云服务推荐系统设计()
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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08期
页码:
139-144
栏目:
应用开发研究
出版日期:
2017-08-10

文章信息/Info

Title:
 Design of Recommender System with Cloud Services of Digital Resource
文章编号:
1673-629X（2017)08-0139-06
作者:
 张龙昌; 张洪锐
 渤海大学 信息科学与技术学院
Author(s):
 ZHANG Long-chang; ZHANG Hong-rui
关键词:
 ; 数字资源云服务; 信息超载; 推荐系统; 满意度
Keywords:
 ; digital resource cloud services; information overload; recommender system; satisfaction
分类号:
TP302
文献标志码:
A
摘要:
 随着云计算技术在数字资源整合中的应用越来越广泛,云服务推荐系统的用户数据集呈现指数级增长的趋势,因而对于数字资源云服务的使用者来说,从海量的数字资源中找到自己真正感兴趣的云服务变得愈加困难,亦即出现了"信息超载"的问题.为了解决"信息超载"问题,设计并实现了数字资源云服务推荐系统.该系统可快速发现满意度最高的云服务并推荐给目标用户,提高了大数据环境下的推荐速度.同时,为了提高数字资源云服务的推荐命中率,所构建的推荐系统采用改进的协同过滤算法,向云服务使用者(待推荐的目标用户)推荐具有相似兴趣行为用户访问过的满意度高的云服务.实验结果表明,数字资源云服务推荐系统可以提高推荐速度,准确地向用户推荐满意度高的数字资源云服务,能够快速提升用户体验.
Abstract:
 As cloud computing technology has been widely used for integrating digital resources,user data set of recommender system of cloud service shows the tendency of exponential growth.Therefore,it is difficult for users of cloud services with digital resource to find their interested cloud services from the huge amounts of digital resources,especially producing the problem of information overload.In order to solve problem of information overload,a recommender system with cloud services of digital resource is designed and implemented,which can quickly find cloud services with the highest satisfaction for target users and improve recommendatory speed in large data environment.Meanwhile,in order to improve hit rate in the process of recommending cloud services with digital resources,the recommendation system has employed improved collaborative filtering algorithm to recommend the favorite cloud services the users with similar interest accessed for target users.The experimental results show that recommender system with cloud services of digital resource has improved the recommendatory speed,and accurately recommended the user cloud services of digital resource with high satisfaction,which has lifted the user experience.

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更新日期/Last Update: 2017-09-21